Essential Mathematical Methods for the Physical Sciences: Student Solution Manual

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Essential Mathematical Methods for the Physical Sciences: Student Solution Manual

STUDENT SOLUTION MANUAL STUDENT SOLUTION MANUAL HOBSON: ESSENTIAL MATHEMATICAL METHODS COVER C M Y BLK This Student S

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STUDENT SOLUTION MANUAL

STUDENT SOLUTION MANUAL

HOBSON: ESSENTIAL MATHEMATICAL METHODS COVER C M Y BLK

This Student Solution Manual provides complete solutions to all the odd-numbered problems in Essential Mathematical Methods for the Physical Sciences. It takes students through each problem step-by-step, so they can clearly see how the solution is reached, and understand any mistakes in their own working. Students will learn by example how to select an appropriate method and improve their problem-solving skills.

ESSENTIAL MATHEMATICAL METHODS for the Physical Sciences

ESSENTIAL MATHEMATICAL METHODS FOR THE PHYSICAL SCIENCES

STUDENT SOLUTION MANUAL

RILEY | HOBSON

ESSENTIAL MATHEMATICAL METHODS for the Physical Sciences

K. F. RILEY | M. P. HOBSON

Student Solution Manual for Essential Mathematical Methods for the Physical Sciences This Student Solution Manual provides complete solutions to all the odd-numbered problems in Essential Mathematical Methods for the Physical Sciences. It takes students through each problem step by step, so they can clearly see how the solution is reached, and understand any mistakes in their own working. Students will learn by example how to select an appropriate method, improving their problem-solving skills. K . F . R i l e y read mathematics at the University of Cambridge and proceeded to a Ph.D. there in theoretical and experimental nuclear physics. He became a Research Associate in elementary particle physics at Brookhaven, and then, having taken up a lectureship at the Cavendish Laboratory, Cambridge, continued this research at the Rutherford Laboratory and Stanford; in particular he was involved in the experimental discovery of a number of the early baryonic resonances. As well as having been Senior Tutor at Clare College, where he has taught physics and mathematics for over 40 years, he has served on many committees concerned with the teaching and examining of these subjects at all levels of tertiary and undergraduate education. He is also one of the authors of 200 Puzzling Physics Problems (Cambridge University Press, 2001). M . P . H o b s o n read natural sciences at the University of Cambridge, specializing in theoretical physics, and remained at the Cavendish Laboratory to complete a Ph.D. in the physics of star formation. As a Research Fellow at Trinity Hall, Cambridge, and subsequently an Advanced Fellow of the Particle Physics and Astronomy Research Council, he developed an interest in cosmology, and in particular in the study of fluctuations in the cosmic microwave background. He was involved in the first detection of these fluctuations using a ground-based interferometer. Currently a University Reader at the Cavendish Laboratory, his research interests include both theoretical and observational aspects of cosmology, and he is the principal author of General Relativity: An Introduction for Physicists (Cambridge University Press, 2006). He is also a Director of Studies in Natural Sciences at Trinity Hall and enjoys an active role in the teaching of undergraduate physics and mathematics.

Essential Mathematical Methods for the Physical Sciences Student Solution Manual

K. F. RILEY University of Cambridge

M. P. HOBSON University of Cambridge

cambridge university press Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, S˜ao Paulo, Delhi, Dubai, Tokyo, Mexico City Cambridge University Press The Edinburgh Building, Cambridge CB2 8RU, UK Published in the United States of America by Cambridge University Press, New York www.cambridge.org Information on this title: www.cambridge.org/9780521141024 C K. Riley and M. Hobson 2011 

This publication is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published 2011 Printed in the United Kingdom at the University Press, Cambridge A catalogue record for this publication is available from the British Library ISBN 978-0-521-14102-4 Paperback

Cambridge University Press has no responsibility for the persistence or accuracy of URLs for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.

Contents

Preface

v

page vii

1

Matrices and vector spaces

2

Vector calculus

27

3

Line, surface and volume integrals

41

4

Fourier series

56

5

Integral transforms

72

6

Higher-order ordinary differential equations

85

7

Series solutions of ordinary differential equations

105

8

Eigenfunction methods for differential equations

116

9

Special functions

128

10

Partial differential equations

138

11

Solution methods for PDEs

149

12

Calculus of variations

166

13

Integral equations

182

14

Complex variables

192

15

Applications of complex variables

200

16

Probability

214

17

Statistics

231

1

Preface

For reasons that are explained in the preface to Essential Mathematical Methods for the Physical Sciences the text of the third edition of Mathematical Methods for Physics and Engineering (MMPE) (Cambridge: Cambridge University Press, 2006) by Riley, Hobson and Bence, after a number of additions and omissions, has been republished as two slightly overlapping texts. Essential Mathematical Methods for the Physical Sciences (EMMPS) contains most of the more advanced material, and specifically develops mathematical methods that can be applied throughout the physical sciences; an augmented version of the more introductory material, principally concerned with mathematical tools rather than methods, is available as Foundation Mathematics for the Physical Sciences. The full text of MMPE, including all of the more specialized and advanced topics, is still available under its original title. As in the third edition of MMPE, the penultimate subsection of each chapter of EMMPS consists of a significant number of problems, nearly all of which are based on topics drawn from several sections of that chapter. Also as in the third edition, hints and outline answers are given in the final subsection, but only to the odd-numbered problems, leaving all even-numbered problems free to be set as unaided homework. This book is the solutions manual for the problems in EMMPS. For the 230 plus oddnumbered problems it contains, complete solutions are available, to both students and their teachers, in the form of this manual; these are in addition to the hints and outline answers given in the main text. For each problem, the original question is reproduced and then followed by a fully worked solution. For those original problems that make internal reference to the main text or to other (even-numbered) problems not included in this solutions manual, the questions have been reworded, usually by including additional information, so that the questions can stand alone. Some further minor rewording has been included to improve the page layout. In many cases the solution given is even fuller than one that might be expected of a good student who has understood the material. This is because we have aimed to make the solutions instructional as well as utilitarian. To this end, we have included comments that are intended to show how the plan for the solution is formulated and have provided the justifications for particular intermediate steps (something not always done, even by the best of students). We have also tried to write each individual substituted formula in the form that best indicates how it was obtained, before simplifying it at the next or a subsequent stage. Where several lines of algebraic manipulation or calculus are needed to obtain a final result, they are normally included in full; this should enable the student to determine whether an incorrect answer is due to a misunderstanding of principles or to a technical error. vii

viii

Preface

As noted above, the original questions are reproduced in full, or in a suitably modified stand-alone form, at the start of each problem. Reference to the main text is not needed provided that standard formulae are known (and a set of tables is available for a few of the statistical and numerical problems). This means that, although it is not its prime purpose, this manual could be used as a test or quiz book by a student who has learned, or thinks that he or she has learned, the material covered in the main text.

1

Matrices and vector spaces

1.1 Which of the following statements about linear vector spaces are true? Where a statement is false, give a counter-example to demonstrate this. (a) (b) (c) (d) (e) (f) (g)

Non-singular N × N matrices form a vector space of dimension N 2 . Singular N × N matrices form a vector space of dimension N 2 . Complex numbers form a vector space of dimension 2. Polynomial functions of x form an infinite-dimensional vector space.  2 Series {a0 , a1 , a2 , . . . , aN } for which N n=0 |an | = 1 form an N -dimensional vector space. Absolutely convergent series form an infinite-dimensional vector space. Convergent series with terms of alternating sign form an infinite-dimensional vector space.

We first remind ourselves that for a set of entities to form a vector space, they must pass five tests: (i) closure under commutative and associative addition; (ii) closure under multiplication by a scalar; (iii) the existence of a null vector in the set; (iv) multiplication by unity leaves any vector unchanged; (v) each vector has a corresponding negative vector. (a) False. The matrix 0N , the N × N null matrix, required by (iii) is not non-singular and is therefore not in the set.     1 0 0 0 (b) Consider the sum of and . The sum is the unit matrix which is not 0 0 0 1 singular and so the set is not closed; this violates requirement (i). The statement is false. (c) The space is closed under addition and multiplication by a scalar; multiplication by unity leaves a complex number unchanged; there is a null vector (= 0 + i0) and a negative complex number for each vector. All the necessary conditions are satisfied and the statement is true. (d) As in the previous case, all the conditions are satisfied and the statement  is true.2 (e) This statement is false. To see why, consider bn = an + an for which N n=0 |bn | = 4 = 1, i.e. the set is not closed (violating (i)), or note that there is no zero vector with unit norm (violating (iii)). (f) True. Note that an absolutely convergent series remains absolutely convergent when the signs of all of its terms are reversed. (g) False. Consider the two series defined by a0 = 12 ,

 n an = 2 − 12 for n ≥ 1;

 n bn = − − 12 for n ≥ 0.

The series that is the sum of {an } and {bn } does not have alternating signs and so closure (required by (i)) does not hold. 1

2

Matrices and vector spaces 1.3 By considering the matrices

 A=

 1 0 , 0 0

 B=

0 3

 0 , 4

show that AB = 0 does not imply that either A or B is the zero matrix but that it does imply that at least one of them is singular.

We have

 AB =

1 0 0 0

 0 3

   0 0 0 = . 4 0 0

Thus AB is the zero matrix 0 without either A = 0 or B = 0. However, AB = 0 ⇒ |A||B| = |0| = 0 and therefore either |A| = 0 or |B| = 0 (or both). 1.5 Using the properties of determinants, solve with a minimum of calculation the following equations for x:     x a a 1 x + 2 x + 4 x − 3      a x b 1  = 0, x x + 5 = 0. (b) x + 3 (a)   x − 2 x − 1 x + 1  a b x 1 a b c 1

(a) In view of the similarities between some rows and some columns, the property most likely to be useful here is that if a determinant has two rows/columns equal (or multiples of each other) then its value is zero. (i) We note that setting x = a makes the first and fourth columns multiples of each other and hence makes the value of the determinant 0; thus x = a is one solution to the equation. (ii) Setting x = b makes the second and third rows equal, and again the determinant vanishes; thus b is another root of the equation. (iii) Setting x = c makes the third and fourth rows equal, and yet again the determinant vanishes; thus c is also a root of the equation. Since the determinant contains no x in its final column, it is a cubic polynomial in x and there will be exactly three roots to the equation. We have already found all three! (b) Here, the presence of x multiplied by unity in every entry means that subtracting rows/columns will lead to a simplification. After (i) subtracting the first column from each of the others, and then (ii) subtracting the first row from each of the others, the determinant becomes     x + 2 2 −5 x + 2 2 −5     x + 3 −3 2  =  1 −5 7     x − 2 1 3   −4 −1 8  = (x + 2)(−40 + 7) + 2(−28 − 8) − 5(−1 − 20) = −33(x + 2) − 72 + 105 = −33x − 33.

3

Matrices and vector spaces

Thus x = −1 is the only solution to the original (linear!) equation. 1.7 Prove the following results involving Hermitian matrices. (a) (b) (c) (d)

If A is Hermitian and U is unitary then U−1 AU is Hermitian. If A is anti-Hermitian then iA is Hermitian. The product of two Hermitian matrices A and B is Hermitian if and only if A and B commute. If S is a real antisymmetric matrix then A = (I − S)(I + S)−1 is orthogonal. If A is given by   cos θ sin θ A= − sin θ cos θ

then find the matrix S that is needed to express A in the above form. (e) If K is skew-Hermitian, i.e. K† = −K, then V = (I + K)(I − K)−1 is unitary.

The general properties of matrices that we will need are (A† )−1 = (A−1 )† and (AB · · · C)T = CT · · · BT AT ,

(AB · · · C)† = C† · · · B† A† .

(a) Given that A = A† and U† U = I, consider (U−1 AU)† = U† A† (U−1 )† = U−1 A(U† )−1 = U−1 A(U−1 )−1 = U−1 AU, i.e. U−1 AU is Hermitian. (b) Given A† = −A, consider (iA)† = −iA† = −i(−A) = iA, i.e. iA is Hermitian. (c) Given A = A† and B = B† . (i) Suppose AB = BA, then (AB)† = B† A† = BA = AB, i.e. AB is Hermitian. (ii) Now suppose that (AB)† = AB. Then BA = B† A† = (AB)† = AB, i.e. A and B commute. Thus, AB is Hermitian ⇐⇒ A and B commute. (d) Given that S is real and ST = −S with A = (I − S)(I + S)−1 , consider AT A = [(I − S)(I + S)−1 ]T [(I − S)(I + S)−1 ] = [(I + S)−1 ]T (I + S)(I − S)(I + S)−1 = (I − S)−1 (I + S − S − S2 )(I + S)−1 = (I − S)−1 (I − S)(I + S)(I + S)−1 = I I = I, i.e. A is orthogonal.

4

Matrices and vector spaces

If A = (I − S)(I + S)−1 , then A + AS = I − S and (A + I)S = I − A, giving S = (A + I)−1 (I − A)  −1   1 + cos θ sin θ 1 − cos θ − sin θ = − sin θ 1 + cos θ sin θ 1 − cos θ    1 1 − cos θ − sin θ 1 + cos θ − sin θ = sin θ 1 − cos θ sin θ 1 + cos θ 2 + 2 cos θ   1 0 −2 sin θ = 2 0 4 cos (θ/2) 2 sin θ   0 − tan(θ/2) = . tan(θ/2) 0 (e) This proof is almost identical to the first section of part (d) but with S replaced by −K and transposed matrices replaced by Hermitian conjugate matrices.  1.9 The commutator X, Y of two matrices is defined by the equation [ X, Y ] = XY − YX. Two anticommuting matrices A and B satisfy A2 = I,

B2 = I,

[ A, B ] = 2iC.

(a) Prove that C = I and that [B, C] = 2iA. (b) Evaluate [ [ [ A, B ], [ B, C ] ], [ A, B ] ]. 2

(a) From AB − BA = 2iC and AB = −BA it follows that AB = iC. Thus, −C2 = iCiC = ABAB = A(−AB)B = −(AA)(BB) = −I I = −I, i.e. C2 = I. In deriving the above result we have used the associativity of matrix multiplication. For the commutator of B and C, [ B, C ] = BC − CB = B(−iAB) − (−i)ABB = −i(BA)B + iAI = −i(−AB)B + iA = iA + iA = 2iA. (b) To evaluate this multiple-commutator expression we must work outwards from the innermost “explicit” commutators. There are three such commutators at the first stage. We also need the result that [ C, A ] = 2iB; this can be proved in the same way as that for [ B, C ] in part (a), or by making the cyclic replacements A → B → C → A in the

5

Matrices and vector spaces

assumptions and their consequences, as proved in part (a). Then we have  [ A, B ], [ B, C ] , [ A, B ] = [ [ 2iC, 2iA ], 2iC ] = −4[ [ C, A ], 2iC ] = −4[ 2iB, 2iC ] = (−4)(−4)[ B, C ] = 32iA.

1.11 A general triangle has angles α, β and γ and corresponding opposite sides a, b and c. Express the length of each side in terms of the lengths of the other two sides and the relevant cosines, writing the relationships in matrix and vector form, using the vectors having components a, b, c and cos α, cos β, cos γ . Invert the matrix and hence deduce the cosine-law expressions involving α, β and γ .

By considering each side of the triangle as the sum of the projections onto it of the other two sides, we have the three simultaneous equations: a = b cos γ + c cos β, b = c cos α + a cos γ , c = b cos α + a cos β. Written in matrix and vector form, Ax = y, they become ⎛ ⎞⎛ ⎞ ⎛ ⎞ 0 c b cos α a ⎝c 0 a ⎠ ⎝ cos β ⎠ = ⎝ b ⎠ . b a 0 cos γ c The matrix A is non-singular, since | A | = 2abc = 0, and therefore has an inverse given by ⎞ ⎛ 2 ab ac −a 1 ⎝ ab −b2 bc ⎠ . A−1 = 2abc ac bc −c2 And so, writing x = A−1 y, we have ⎛ ⎞ ⎛ 2 cos α −a 1 ⎝ cos β ⎠ = ⎝ ab 2abc cos γ ac

ab −b2 bc

⎞⎛ ⎞ ac a bc ⎠ ⎝ b ⎠ . −c2 c

From this we can read off the cosine-law equation cos α =

b2 + c2 − a 2 1 (−a 3 + ab2 + ac2 ) = , 2abc 2bc

and the corresponding expressions for cos β and cos γ .

6

Matrices and vector spaces 1.13 Determine which of the matrices below are mutually commuting, and, for those that are, demonstrate that they have a complete set of eigenvectors in common:     6 −2 1 8 A= , B= , −2 9 8 −11     −9 −10 14 2 C= , D= . −10 5 2 11

To establish the result we need to examine all pairs of products.    6 −2 1 8 AB = −2 9 8 −11   −10 70 = 70 −115    1 8 6 −2 = BA. = 8 −11 −2 9    −9 −10 6 −2 AC = −10 5 −2 9     −34 −70 −34 −72 = = −72 65 −70 65    −9 −10 6 −2 = = CA. −10 5 −2 9 Continuing in this way, we find: 

 80 −10 AD = = DA. −10 95     −89 30 −89 38 BC = = = CB. 38 −135 30 −135   30 90 BD = = DB. 90 −105     −146 −128 −146 −130 CD = = = DC. −130 35 −128 35 These results show that whilst A, B and D are mutually commuting, none of them commutes with C. We could use any of the three mutually commuting matrices to find the common set (actually a pair, as they are 2 × 2 matrices) of eigenvectors. We arbitrarily choose A. The eigenvalues of A satisfy   6 − λ −2     −2 9 − λ = 0, λ2 − 15λ + 50 = 0, (λ − 5)(λ − 10) = 0.

7

Matrices and vector spaces

For λ = 5, an eigenvector (x y)T must satisfy x − 2y = 0, whilst, for λ = 10, 4x + 2y = 0. Thus a pair of independent eigenvectors of A are (2 1)T and (1 −2)T . Direct substitution verifies that they are also eigenvectors of B and D with pairs of eigenvalues 5, −15 and 15, 10, respectively. 1.15 Solve the simultaneous equations 2x + 3y + z = 11, x + y + z = 6, 5x − y + 10z = 34.

To eliminate z, (i) subtract the second equation from the first and (ii) subtract 10 times the second equation from the third. x + 2y = 5, −5x − 11y = −26. To eliminate x add 5 times the first equation to the second −y = −1. Thus y = 1 and, by resubstitution, x = 3 and z = 2. 1.17 Show that the following equations have solutions only if η = 1 or 2, and find them in these cases: x + y + z = 1,

(i)

x + 2y + 4z = η,

(ii)

x + 4y + 10z = η .

(iii)

2

Expressing the equations in the form Ax = b, we first need to evaluate |A| as a preliminary to determining A−1 . However, we find that |A| = 1(20 − 16) + 1(4 − 10) + 1(4 − 2) = 0. This result implies both that A is singular and has no inverse, and that the equations must be linearly dependent. Either by observation or by solving for the combination coefficients, we see that for the LHS this linear dependence is expressed by 2 × (i) + 1 × (iii) − 3 × (ii) = 0. For a consistent solution, this must also be true for the RHSs, i.e. 2 + η2 − 3η = 0. This quadratic equation has solutions η = 1 and η = 2, which are therefore the only values of η for which the original equations have a solution. As the equations are linearly dependent, we may use any two to find these allowed solutions; for simplicity we use the first two in each case.

8

Matrices and vector spaces

For η = 1, x + y + z = 1,

x + 2y + 4z = 1 ⇒ x1 = (1 + 2α

− 3α

α)T .

For η = 2, x + y + z = 1,

x + 2y + 4z = 2 ⇒ x2 = (2α

1 − 3α

α)T .

In both cases there is an infinity of solutions as α may take any finite value. 1.19 Make an LU decomposition of the matrix



3 A = ⎝1 2 and hence solve Ax = b, where (i) b = (21

Using the notation



1 A = ⎝L21 L31

0 1 L32

6 0 −2

⎞ 9 5 ⎠ 16

9 28)T , (ii) b = (21 7

⎞⎛ U11 0 0⎠ ⎝ 0 1 0

U12 U22 0

22)T .

⎞ U13 U23 ⎠ , U33

and considering rows and columns alternately in the usual way for an LU decomposition, we require the following to be satisfied. 1st row: U11 = 3, U12 = 6, U13 = 9. 1st col: L21 U11 = 1, L31 U11 = 2 ⇒ L21 = 13 , L31 = 23 . 2nd row: L21 U12 + U22 = 0, L21 U13 + U23 = 5 ⇒ U22 = −2, 2nd col: L31 U12 + L32 U22 = −2 ⇒ L32 = 3. 3rd row: L31 U13 + L32 U23 + U33 = 16 ⇒ U33 = 4. Thus



1

L = ⎝3

1 2 3

⎞ 0 0 1 0⎠ 3 1



and

3 ⎝ U= 0 0

6 −2 0

U23 = 2.

⎞ 9 2⎠ . 4

To solve Ax = b with A = LU, we first determine y from Ly = b and then solve Ux = y for x. (i) For Ax = (21 9 28)T , we first solve ⎞⎛ ⎞ ⎛ ⎞ ⎛ 1 0 0 21 y1 ⎝ 31 1 0⎠ ⎝ y2 ⎠ = ⎝ 9 ⎠ . 2 28 y3 3 1 3 This can be done, almost by inspection, to give y = (21 2 8)T . We can now write Ux = y explicitly as ⎛ ⎞⎛ ⎞ ⎛ ⎞ 21 3 6 9 x1 ⎝0 −2 2⎠ ⎝ x2 ⎠ = ⎝ 2 ⎠ 8 x3 0 0 4 to give, equally easily, that the solution to the original matrix equation is x = (−1

1

2)T .

9

Matrices and vector spaces

(ii) To solve Ax = (21 7 22)T we use exactly the same forms for L and U, but the new values for the components of b, to obtain y = (21 0 8)T leading to the solution x = (−3 2 2)T . 1.21 Use the Cholesky decomposition method to determine whether the following matrices are positive definite. For each that is, determine the corresponding lower diagonal matrix L : √ ⎞ ⎛ ⎞ ⎛ 3 2 1 3 5 0 A = ⎝1 3 −1⎠ , B = ⎝√0 3 0 ⎠ . 3 −1 1 3 0 3

The matrix A is real and so we seek a real lower-diagonal matrix L such that LLT = A. In order to avoid a lot of subscripts, we use lower-case letters as the non-zero elements of L: ⎛

a ⎝b d

0 c e

⎞⎛ 0 a 0 ⎠ ⎝0 f 0

b c 0

⎞ ⎛ ⎞ d 2 1 3 e ⎠ = ⎝1 3 −1⎠ . f 3 −1 1

Firstly, from A11 , a 2 = 2. Since an overall negative sign multiplying the elements of L √ √ is irrelevant, we may choose a = + 2. Next, ba = A12 = 1, implying that b = 1/ 2. √ Similarly, d = 3/ 2. From the second row of A we have  2 2 b + c = 3 ⇒ c = 52 ,     bd + ce = −1 ⇒ e = 25 −1− 32 = − 52 . And, from the final row, d 2 + e2 + f 2 = 1



 1/2 √ f = 1− 92 − 52 = −6.

That f is imaginary shows that A is not a positive definite matrix. The corresponding argument (keeping the same symbols but with different numerical values) for the matrix B is as follows. Firstly, from A11 , a 2 = 5. Since an overall negative sign multiplying the elements of L is √ irrelevant, we may choose a = + 5. Next, ba = B12 = 0, implying that b = 0. Similarly, √ √ d = 3/ 5. From the second row of B we have b2 + c2 = 3



bd + ce = 0



√ 3,  e = 13 (0 − 0) = 0. c=

And, from the final row, d 2 + e2 + f 2 = 3



f = (3 −

3 5

− 0)1/2 =



12 . 5

10

Matrices and vector spaces

Thus all the elements of L have been calculated and found to be real and, in summary, ⎛√ ⎞ 5 0 0 √ ⎜ 3 0 ⎟ L = ⎝0 ⎠. 3 12 0 5 5 That LLT = B can be confirmed by substitution. 1.23 Find three real orthogonal column matrices, each of which is a simultaneous eigenvector of ⎛ ⎞ ⎛ ⎞ 0 0 1 0 1 1 A = ⎝0 1 0⎠ and B = ⎝1 0 1⎠. 1 0 0 1 1 0

We first note that



1 AB = ⎝1 0

1 0 1

⎞ 0 1⎠ = BA. 1

The two matrices commute and so they will have a common set of eigenvectors. The eigenvalues of A are given by   −λ 0 1    0 1 − λ 0  = (1 − λ)(λ2 − 1) = 0,    1 0 −λ i.e. λ = 1, λ = 1 and λ = −1, with corresponding eigenvectors e1 = (1 y1 1)T , e2 = (1 y2 1)T and e3 = (1 0 −1)T . For these to be mutually orthogonal requires that y1 y2 = −2. The third vector, e3 , is clearly an eigenvector of B with eigenvalue μ3 = −1. For e1 or 2 e to be an eigenvector of B with eigenvalue μ requires ⎛ ⎞⎛ ⎞ ⎛ ⎞ 0−μ 1 1 1 0 ⎝ 1 0−μ 1 ⎠⎝y ⎠ = ⎝0⎠; 1 1 0−μ 1 0 i.e. and giving

−μ + y + 1 = 0, 1 − μy + 1 = 0, 2 − + y + 1 = 0, y ⇒ y 2 + y − 2 = 0, ⇒ y = 1 or

−2.

Thus, y1 = 1 with μ1 = 2, whilst y2 = −2 with μ2 = −1. The common eigenvectors are thus e1 = (1

1)T , e2 = (1 −2 1)T , e3 = (1 0 −1)T .  We note, as a check, that i μi = 2 + (−1) + (−1) = 0 = Tr B. 1

11

Matrices and vector spaces 1.25 Given that A is a real symmetric matrix with normalized eigenvectors ei , obtain the coefficients αi involved when column matrix x, which is the solution of

is expanded as x =

Ax − μx = v,

 i

αi e . Here μ is a given constant and v is a given column matrix.

(a) Solve (∗) when



2 A = ⎝1 0 μ = 2 and v = (1 2 3)T . (b) Would (∗) have a solution if (i) μ = 1 and v = (1 find it.

Let x =

 i

(∗)

i

1 2 0

⎞ 0 0⎠, 3 2 3)T , (ii) v = (2 2

3)T ? Where it does,

αi ei , where Aei = λi ei . Then  i

Ax − μx = v,  Aαi e − μαi ei = v,



i

i

 λi αi e − μαi ei = v, i

i

αj =

(ej )† v . λj − μ

To obtain the last line we have used the mutual orthogonality of the eigenvectors. We note, in passing, that if μ = λj for any j there is no solution unless (ej )† v = 0. (a) To obtain the eigenvalues of the given matrix A, consider 0 = |A − λI| = (3 − λ)(4 − 4λ + λ2 − 1) = (3 − λ)(3 − λ)(1 − λ). The eigenvalues, and a possible set of corresponding normalized eigenvectors, are therefore, for

λ = 3,

e1 = (0

for

λ = 3,

e2 = 2−1/2 (1

for

λ = 1,

e3 = 2−1/2 (1 −1 0)T .

0

1)T ; 1

0)T ;

Since λ = 3 is a degenerate eigenvalue, there are infinitely many acceptable pairs of orthogonal eigenvectors corresponding to it; any pair of vectors of the form (ai , ai , bi ) with 2a1 a2 + b1 b2 = 0 will suffice. The pair given is just about the simplest choice possible. With μ = 2 and v = (1 2 3)T , √ √ 3 3/ 2 −1/ 2 , α2 = , α3 = . α1 = 3−2 3−2 1−2

12

Matrices and vector spaces

Thus the solution vector is ⎛ ⎞ ⎛ ⎞ ⎛ ⎞ ⎛ ⎞ 0 1 1 2 3 1 ⎝ ⎠ 1 1 ⎝ ⎝ ⎠ ⎠ ⎝ 1 +√ √ −1 = 1 ⎠ . x=3 0 +√ √ 2 2 2 2 1 0 0 3 (b) If μ = 1 then it is equal to the third eigenvalue and a solution is only possible if (e3 )† v = 0. √ For (i) v = (1 2 3)T , (e3 )† v = −1/ 2 and so no solution is possible. For (ii) v = (2 2 3)T , (e3 )† v = 0, and so a solution is possible. The other scalar √ products needed are (e1 )† v = 3 and (e2 )† v = 2 2. For this vector v the solution to the equation is ⎛ ⎞ ⎛ ⎞ ⎛ ⎞ √ 1 1 0 3 ⎝ ⎠ 2 2 1 ⎝ ⎠ ⎝ ⎠ 1 = 1 . 0 + x= √ 3−1 3−1 2 3 0 1 2 [The solutions to both parts can be checked by resubstitution.] 1.27 By finding the eigenvectors of the Hermitian matrix   10 3i H= , −3i 2 construct a unitary matrix U such that U† HU = , where  is a real diagonal matrix.

We start by finding the eigenvalues of H using  10 − λ   −3i

 3i  = 0, 2 − λ

20 − 12λ + λ2 − 3 = 0, λ=1

or

11.

As expected for an Hermitian matrix, the eigenvalues are real. For λ = 1 and normalized eigenvector (x y)T , 9x + 3iy = 0



For λ = 11 and normalized eigenvector (x −x + 3iy = 0



x1 = (10)−1/2 (1

3i)T .

y)T , x2 = (10)−1/2 (3i

1)T .

Again as expected, (x1 )† x2 = 0, thus verifying the mutual orthogonality of the eigenvectors. It should be noted that the normalization factor is determined by (xi )† xi = 1 (and not by (xi )T xi = 1).

13

Matrices and vector spaces

We now use these normalized eigenvectors of H as the columns of the matrix U and check that it is unitary:     1 1 1 3i 1 −3i U= √ , U† = √ , 1 10 3i 1 10 −3i  1 1 UU = 10 3i †

3i 1



1 −3i

−3i 1



 1 10 = 10 0

 0 = I. 10

U has the further property that

    1 1 10 3i 1 −3i 1 U HU = √ √ −3i 2 1 10 −3i 10 3i    1 1 −3i 1 33i = 1 3i 11 10 −3i     1 10 0 1 0 = = = . 0 11 10 0 110 †

3i 1



That the diagonal entries of  are the eigenvalues of H is in accord with the general theory of normal matrices. 1.29 Given that the matrix



2 A = ⎝ −1 0

−1 2 −1

⎞ 0 −1 ⎠ 2

has two eigenvectors of the form (1 y 1)T , use the stationary property of the expression J (x) = xT Ax/(xT x) to obtain the corresponding eigenvalues. Deduce the third eigenvalue.

Since A is real and symmetric, each eigenvalue λ is real. Further, from the first component of Ax = λx, we have that 2 − y = λ, showing that y is also real. Considered as a function of a general vector of the form (1 y 1)T , the quadratic form xT Ax can be written explicitly as ⎛ ⎞⎛ ⎞ 2 −1 0 1 xT Ax = (1 y 1) ⎝−1 2 −1⎠ ⎝ y ⎠ 0 −1 2 1 ⎛ ⎞ 2−y ⎝ = (1 y 1) 2y − 2 ⎠ 2−y = 2y 2 − 4y + 4. The scalar product xT x has the value 2 + y 2 , and so we need to find the stationary values of I=

2y 2 − 4y + 4 . 2 + y2

14

Matrices and vector spaces

These are given by 0=

dI (2 + y 2 )(4y − 4) − (2y 2 − 4y + 4)2y = dy (2 + y 2 )2 0 = 4y 2 − 8, √ y = ± 2.

The corresponding eigenvalues are the values of I at the stationary points: √ √ √ 2(2) − 4 2 + 4 for y = 2, λ1 = = 2 − 2; 2+2 √ √ √ 2(2) + 4 2 + 4 for y = − 2, λ2 = = 2 + 2. 2+2 The final eigenvalue can be found using the fact that the sum of the eigenvalues is equal to the trace of the matrix; so √ √ λ3 = (2 + 2 + 2) − (2 − 2) − (2 + 2) = 2.

1.31 The equation of a particular conic section is Q ≡ 8x12 + 8x22 − 6x1 x2 = 110. Determine the type of conic section this represents, the orientation of its principal axes, and relevant lengths in the directions of these axes.



 8 −3 The eigenvalues of the matrix associated with the quadratic form on the LHS −3 8 (without any prior scaling) are given by   8 − λ −3   0 =  −3 8 − λ = λ2 − 16λ + 55 = (λ − 5)(λ − 11). Referred to the corresponding eigenvectors as axes, the conic section (an ellipse since both eigenvalues are positive) will take the form y12 y2 5y12 + 11y22 = 110 or, in standard form, + 2 = 1. 22 10 √ √ Thus the semi-axes are of lengths 22 and 10 ; the former is in the direction of the vector (x1 x2 )T given by (8 − 5)x1 − 3x2 = 0, i.e. it is the line x1 = x2 . The other principal axis will be the line at right angles to this, namely the line x1 = −x2 . 1.33 Find the direction of the axis of symmetry of the quadratic surface 7x 2 + 7y 2 + 7z2 − 20yz − 20xz + 20xy = 3.

The straightforward, but longer, solution to this problem is as follows.

15

Matrices and vector spaces

Consider the characteristic polynomial of the matrix associated with the quadratic surface, namely,   7 − λ 10 −10   7 − λ −10  f (λ) =  10  −10 −10 7 − λ = (7 − λ)(−51 − 14λ + λ2 ) + 10(30 + 10λ) − 10(−30 − 10λ) = −λ3 + 21λ2 + 153λ + 243. If the quadratic surface has an axis of symmetry, it must have two equal major axes (perpendicular to it), and hence the characteristic equation must have a repeated root. This same root will therefore also be a root of df/dλ = 0, i.e. of −3λ2 + 42λ + 153 = 0, λ2 − 14λ − 51 = 0, λ = 17

or

− 3.

Substitution shows that −3 is a root (and therefore a double root) of f (λ) = 0, but that 17 is not. The non-repeated root can be calculated as the trace of the matrix minus the repeated roots, i.e. 21 − (−3) − (−3) = 27. It is the eigenvector that corresponds to this eigenvalue that gives the direction (x y z)T of the axis of symmetry. Its components must satisfy (7 − 27)x + 10y − 10z = 0, 10x + (7 − 27)y − 10z = 0. The axis of symmetry is therefore in the direction (1 1 −1)T . A more subtle solution is obtained by noting that setting λ = −3 makes all three of the rows (or columns) of the determinant multiples of each other, i.e. it reduces the determinant to rank one. Thus −3 is a repeated root of the characteristic equation and the third root is 21 − 2(−3) = 27. The rest of the analysis is as above. We note in passing that, as two eigenvalues are negative and equal, the surface is the hyperboloid of revolution obtained by rotating a (two-branched) hyperbola about its axis of symmetry. Referred to this axis and two others forming a mutually orthogonal set, the equation of the quadratic surface takes the form −3χ 2 − 3η2 + 27ζ 2 = 3 and so the tips of the two “nose cones” (χ = η = 0) are separated by 23 of a unit. 1.35 This problem demonstrates the reverse of the usual procedure of diagonalizing a matrix. (a) Rearrange the result A = S−1 AS (which shows how to make a change of basis that diagonalizes A) so as to express the original matrix A in terms of the unitary matrix S and the diagonal matrix A . Hence show how to construct a matrix A that has given eigenvalues and given (orthogonal) column matrices as its eigenvectors. (b) Find the matrix that has as eigenvectors (1 2 1)T , (1 −1 1)T and (1 0 −1)T and corresponding eigenvalues λ, μ and ν. (c) Try a particular case, say λ = 3, μ = −2 and ν = 1, and verify by explicit solution that the matrix so found does have these eigenvalues.

16

Matrices and vector spaces

(a) Since S is unitary, we can multiply the given result on the left by S and on the right by S† to obtain SA S† = SS−1 ASS† = (I) A (I) = A. More explicitly, in terms of the eigenvalues and normalized eigenvectors xi of A, A = (x1

x2

···

xn )(x1

···

x2

xn )† .

Here  is the diagonal matrix that has the eigenvalues of A as its diagonal elements. Now, given normalized orthogonal column matrices and n specified values, we can use this result to construct a matrix that has the column matrices as eigenvectors and the values as eigenvalues. (b) The normalized versions of the given column vectors are 1 √ (1 6

2

1)T ,

1 √ (1 −1 1)T , 3

1 √ (1 2

0 −1)T ,

and the orthogonal matrix S can be constructed using these as its columns: ⎛

√ 1 2 √ 1 S = √ ⎝2 − 2 √ 6 1 2

√ ⎞ 3 0 ⎠. √ − 3

The required matrix A can now be formed as SS† : ⎛ ⎞ ⎞⎛ √ √ ⎞⎛ 1 2 3 λ 0 0 1 2 1 √ √ √ √ 1⎝ 2 − 2 0 ⎠ ⎝ 0 μ 0⎠ ⎝ 2 − 2 2⎠ A= √ √ √ √ 6 1 2 − 3 3 0 − 3 0 0 ν ⎞ ⎛ √ √ ⎞⎛ 1 2 3 λ 2λ λ √ √ √ √ 1 0 ⎠ ⎝ 2μ − 2μ 2μ ⎠ = ⎝2 − 2 √ √ √ √ 6 3ν 0 − 3ν 1 2 − 3 ⎛ ⎞ λ + 2μ + 3ν 2λ − 2μ λ + 2μ − 3ν 1⎝ 2λ − 2μ 4λ + 2μ 2λ − 2μ ⎠ . = 6 λ + 2μ − 3ν 2λ − 2μ λ + 2μ + 3ν (c) Setting λ = 3, μ = −2 and ν = 1, as a particular case, gives A as ⎛ 2 10 1⎝ 10 8 A= 6 −4 10

⎞ −4 10 ⎠ . 2

We complete the problem by solving for the eigenvalues of A in the usual way. To avoid working with fractions, and any confusion with the value λ = 3 used when constructing

17

Matrices and vector spaces

A, we will find the eigenvalues of 6A and denote them by η. 0 = | 6A − ηI |  2 − η 10  8−η =  10  −4 10

 −4  10  2 − η

= (2 − η)(η2 − 10η − 84) + 10(10η − 60) − 4(132 − 4η) = −η3 + 12η2 + 180η − 1296 = −(η − 6)(η2 − 6η − 216) = −(η − 6)(η + 12)(η − 18). Thus 6A has eigenvalues 6, −12 and 18; the values for A itself are 1, −2 and 3, as expected. 1.37 A more general form of expression for the determinant of a 3 × 3 matrix A than (1.45) is given by |A| lmn = Ali Amj Ank ij k .

(1.1)

The former could, as stated earlier in this chapter, have been written as |A| = ij k Ai1 Aj 2 Ak3 . The more general form removes the explicit mention of 1, 2, 3 at the expense of an additional Levi–Civita symbol; the form of (1.1) can be readily extended to cover a general N × N matrix. Use this more general form to prove properties (i), (iii), (v), (vi) and (vii) of determinants stated in Subsection 1.9.1. Property (iv) is obvious by inspection. For definiteness take N = 3, but convince yourself that your methods of proof would be valid for any positive integer N .

A full account of the answer to this problem is given in the Hints and answers section at the end of the chapter, almost as if it were part of the main text. The reader is referred there for the details. 1.39 Three coupled pendulums swing perpendicularly to the horizontal line containing their points of suspension, and the following equations of motion are satisfied: −mx¨1 = cmx1 + d(x1 − x2 ), −M x¨2 = cMx2 + d(x2 − x1 ) + d(x2 − x3 ), −mx¨3 = cmx3 + d(x3 − x2 ), where x1 , x2 and x3 are measured from the equilibrium points; m, M and m are the masses of the pendulum bobs; and c and d are positive constants. Find the normal frequencies of the system and sketch the corresponding patterns of oscillation. What happens as d → 0 or d → ∞?

In a normal mode all three coordinates xi oscillate with the same frequency and with fixed relative phases. When this is represented by solutions of the form xi = Xi cos ωt, where

18

Matrices and vector spaces

the Xi are fixed constants, the equations become, in matrix and vector form, ⎛ ⎞⎛ ⎞ cm + d − mω2 −d 0 X1 ⎝ ⎠ ⎝ X2 ⎠ = 0. −d −d cM + 2d − Mω2 X3 0 −d cm + d − mω2 For there to be a non-trivial solution to these simultaneous homogeneous equations, we need    (c − ω2 )m + d −d 0   2   −d −d (c − ω )M + 2d 0=  2  0 −d (c − ω )m + d    (c − ω2 )m + d 0 −(c − ω2 )m − d    −d −d (c − ω2 )M + 2d =   2  0 −d (c − ω )m + d  = [(c − ω2 )m + d] {[(c − ω2 )M + 2d] [(c − ω2 )m + d] − d 2 − d 2 } = (cm − mω2 + d)(c − ω2 )[Mm(c − ω2 ) + 2dm + dM]. Thus, the normal (angular) frequencies are given by ω2 = c,

ω2 = c +

d m

and

ω2 = c +

d 2d + . M m

If the solution column matrix is X = (X1 X2 X3 )T , then (i) for ω2 = c, the components of X must satisfy dX1 − dX2 = 0, −dX1 + 2dX2 − dX3 = 0, (ii) for ω2 = c +



X1 = (1

1

1)T ;

d , we have m 

−dX1 + −



−dX2 = 0,

dM + 2d X2 − dX3 = 0, m



X2 = (1

2d d + , the components must satisfy M m    d 2d − m + d X1 − dX2 = 0, − M m     2d d 3 −dX2 + − − m + d X3 = 0, ⇒ X = 1 M m

0 −1)T ;

(iii) for ω2 = c +

2m − M

T 1 .

The corresponding patterns are shown in Figure 1.1. If d → 0, the three oscillations decouple and each pendulum swings independently √ with angular frequency c. If d → ∞, the three pendulums become rigidly coupled. The second and third modes have (theoretically) infinite frequency and therefore zero amplitude. The only sustainable

19

Matrices and vector spaces

1 m

2 M

3 m

(a)

ω2 = c +

d m

(b)

ω2 = c

(c)

ω2 = c + 2d + d M m

kM

kM 2km

Figure 1.1 The normal modes, as viewed from above, of the coupled pendulums in Problem 1.39.

mode is the one shown as case (b) in the figure; one in which all the pendulums swing as √ a single entity with angular frequency c. 1.41 Find the normal frequencies of a system consisting of three particles of masses m1 = m, m2 = μ m, m3 = m connected in that order in a straight line by two equal light springs of force constant k. Describe the corresponding modes of oscillation. Now consider the particular case in which μ = 2. (a) Show that the eigenvectors derived above have the expected orthogonality properties with respect to both the kinetic energy matrix A and the potential energy matrix B. (b) For the situation in which the masses are released from rest with initial displacements (relative to their equilibrium positions) of x1 = 2 , x2 = − and x3 = 0, determine their subsequent motions and maximum displacements.

Let the coordinates of the particles, x1 , x2 , x3 , be measured from their equilibrium positions, at which the springs are neither extended nor compressed. The kinetic energy of the system is simply   T = 12 m x˙12 + μ x˙22 + x˙32 , whilst the potential energy stored in the springs takes the form  V = 12 k (x2 − x1 )2 + (x3 − x2 )2 .

20

Matrices and vector spaces

The kinetic- and potential-energy symmetric matrices are thus ⎛ ⎛ ⎞ 1 0 0 1 −1 m⎝ k 0 μ 0⎠ , A= B = ⎝−1 2 2 2 0 0 1 0 −1

⎞ 0 −1⎠ . 1

To find the normal frequencies we have to solve |B − ω2 A| = 0. Thus, writing mω2 /k = λ, we have   1 − λ −1 0   0 =  −1 2 − μ λ −1   0 −1 1 − λ = (1 − λ)(2 − μλ − 2λ + μλ2 − 1) + (−1 + λ) = (1 − λ)λ(−μ − 2 + μλ), which leads to λ = 0, 1 or 1 + 2/μ. The normalized eigenvectors corresponding to the first two eigenvalues can be found by inspection and are ⎛ ⎞ ⎛ ⎞ 1 1 1 1 x2 = √ ⎝ 0 ⎠ . x1 = √ ⎝ 1 ⎠ , 3 1 2 −1 The components of the third eigenvector must satisfy −

2 x1 − x2 = 0 and μ

x2 −

2 x3 = 0. μ

The normalized third eigenvector is therefore 1



2 x = 1 − 2 μ 2 + (4/μ ) 3

T 1 .

The physical motions associated with these normal modes are as follows. The first, with λ = ω = 0 and all the xi equal, merely describes bodily translation of the whole system, with no (i.e. zero-frequency) internal oscillations. In the second solution, the central particle remains stationary, x2 = 0, whilst the other two oscillate with equal amplitudes in antiphase with each other. This motion has frequency ω = (k/m)1/2 , the same as that for the oscillations of a single mass m suspended from a single spring of force constant k. The final and most complicated of the three normal modes has angular frequency ω = {[(μ + 2)/μ](k/m)}1/2 , and involves a motion of the central particle which is in antiphase with that of the two outer ones and which has an amplitude 2/μ times as great. In this motion the two springs are compressed and extended in turn. We also note that in the second and third normal modes the center of mass of the system remains stationary. √ Now setting μ = 2, we have as the three normal (angular) frequencies 0,  and 2, where 2 = k/m. The corresponding (unnormalized) eigenvectors are x1 = (1

1

1)T ,

x2 = (1

0 −1)T ,

x3 = (1 −1 1)T .

21

Matrices and vector spaces

(a) The matrices A and B have the forms ⎛ ⎞ 1 0 0 A = ⎝0 2 0⎠ , 0 0 1



⎞ 1 −1 0 B = ⎝−1 2 −1⎠ . 0 −1 1

To verify the standard orthogonality relations we need to show that the quadratic forms (xi )† Axj and (xi )† Bxj have zero value for i = j . Direct evaluation of all the separate cases is as follows: (x1 )† Ax2 = 1 + 0 − 1 = 0, (x1 )† Ax3 = 1 − 2 + 1 = 0, (x2 )† Ax3 = 1 + 0 − 1 = 0, (x1 )† Bx2 = (x1 )† (1

0 −1)T = 1 + 0 − 1 = 0,

(x1 )† Bx3 = (x1 )† (2

− 4 2)T = 2 − 4 + 2 = 0,

(x2 )† Bx3 = (x2 )† (2

− 4 2)T = 2 + 0 − 2 = 0.

If (xi )† Axj has zero value then so does (xj )† Axi (and similarly for B). So there is no need to investigate the other six possibilities and the verification is complete. (b) In order to determine the behavior of the system we need to know which modes are present in the initial configuration. Each contributory mode will subsequently oscillate with its own frequency. In order to carry out this initial decomposition we write (2



0)T = a (1

1

1)T + b (1

0 −1)T + c (1 −1 1)T ,

from which it is clear that a = 0, b = and c = . As each mode vibrates with its own frequency, the subsequent displacements are given by √ x1 = (cos t + cos 2t), √ x2 = − cos 2t, √ x3 = (− cos t + cos 2t). √ Since  and 2 are not rationally related, at some times the two modes will, for all practical purposes (but not mathematically), be in phase and, at other times, be out of phase. Thus the maximum displacements will be x1 (max) = 2 , x2 (max) = and x3 (max) = 2 . 1.43 It is shown in physics and engineering textbooks that circuits containing capacitors and inductors can be analyzed by replacing a capacitor of capacitance C by a “complex impedance” 1/(iωC) and an inductor of inductance L by an impedance iωL, where ω is the angular frequency of the currents flowing and i 2 = −1. Use this approach and Kirchhoff’s circuit laws to analyze the circuit shown in Figure 1.2 and obtain three linear equations governing the currents I1 , I2 and I3 . Show that the only possible frequencies of self-sustaining currents satisfy either (a) ω2 LC = 1 or (b) 3ω2 LC = 1. Find the corresponding current patterns and, in each case, by identifying parts of the circuit in which no current flows, draw an equivalent circuit that contains only one capacitor and one inductor.

22

Matrices and vector spaces

C P

I1

Q

U L

L S

I2

C

T

C

I3

R

Figure 1.2 The circuit and notation for Problem 1.43.

We apply Kirchhoff’s laws to the three closed loops P QU P , SU T S and T U RT and obtain, respectively, 1 I1 + iωL(I1 − I3 ) + iωL(I1 − I2 ) = 0, iωC 1 iωL(I2 − I1 ) + I2 = 0, iωC 1 I3 = 0. iωL(I3 − I1 ) + iωC For these simultaneous homogeneous linear equations to be consistent, it is necessary that     1   + 2iωL −iωL −iωL    λ − 2  iωC 1 1     1 = 1 λ−1 0  , 0 =  −iωL + iωL 0   iωC   1  0 λ − 1 1    −iωL + iωL 0 iωC where, after dividing all entries by −iωL, we have written the combination (LCω2 )−1 as λ to save space. Expanding the determinant gives 0 = (λ − 2)(λ − 1)2 − (λ − 1) − (λ − 1) = (λ − 1)(λ2 − 3λ + 2 − 2) = λ(λ − 1)(λ − 3). Only the non-zero roots are of practical physical interest, and these are λ = 1 and λ = 3. (a) The first of these eigenvalues has an eigenvector I1 = (I1 I2 I3 )T that satisfies −I1 + I2 + I3 = 0, I1 = 0



I1 = (0 1

−1)T .

Thus there is no current in P Q and the capacitor in that link can be ignored. Equal currents circulate, in opposite directions, in the other two loops and, although the link T U carries both, there is no transfer between the two loops. Each loop is therefore equivalent to a capacitor of capacitance C in parallel with an inductor of inductance L.

23

Matrices and vector spaces

(b) The second eigenvalue has an eigenvector I2 = (I1

I2

I3 )T that satisfies

I1 + I2 + I3 = 0, I1 + 2I2 = 0



I2 = (−2

1

1)T .

In this mode there is no current in T U and the circuit is equivalent to an inductor of inductance L + L in parallel with a capacitor of capacitance 3C/2; this latter capacitance is made up of C in parallel with the capacitance equivalent to two capacitors C in series, i.e. in parallel with 12 C. Thus, the equivalent single components are an inductance of 2L and a capacitance of 3C/2. 1.45 A double pendulum consists of two identical uniform rods, each of length  and mass M, smoothly jointed together and suspended by attaching the free end of one rod to a fixed point. The system makes small oscillations in a vertical plane, with the angles made with the vertical by the upper and lower rods denoted by θ1 and θ2 , respectively. The expressions for the kinetic energy T and the potential energy V of the system are (to second order in the θi )   T ≈ Ml 2 83 θ˙12 + 2θ˙1 θ˙2 + 23 θ˙22 ,   V ≈ Mgl 32 θ12 + 12 θ22 . Determine the normal frequencies of the system and find new variables ξ and η that will reduce these two expressions to diagonal form, i.e. to a1 ξ˙ 2 + a2 η˙ 2

and b1 ξ 2 + b2 η2 .

To find the new variables we will use the following result. If the reader is not familiar with it, a standard textbook should be consulted. If Q1 = uT Au and Q2 = uT Bu are two real symmetric quadratic forms and un are those column matrices that satisfy Bun = λn Aun , then the matrix P whose columns are the vectors un is such that the change of variables u = Pv reduces both quadratic forms simultaneously to sums of squares, i.e. Q1 = vT Cv and Q2 = vT Dv, with both C and D diagonal. Further points to note are: (i) that for the ui as determined above, (um )T Aun = 0 if m = n and similarly if A is replaced by B; (ii) that P is not in general an orthogonal matrix, even if the vectors un are normalized. (iii) In the special case that A is the identity matrix I: the above procedure is the same as diagonalizing B; P is an orthogonal matrix if normalized vectors are used; mutual orthogonality of the eigenvectors takes on its usual form.

This problem is a physical example to which the above mathematical result can be applied, the two real symmetric (actually positive-definite) matrices being the kinetic and potential energy matrices.     8 3 1 0 ω2 l A= 3 2 , B= 2 1 with λi = i . g 1 3 0 2

24

Matrices and vector spaces

We find the normal frequencies by solving 0 = |B − λA|  3 − 8 λ  = 2 3  −λ = ⇒

3 4

− 73 λ +

1 2

 −λ   − 23 λ

16 2 λ 9

− λ2

0 = 28λ2 − 84λ + 27.

Thus, λ = 2.634 or λ = 0.3661, and the normal frequencies are (2.634g/ l)1/2 and (0.3661g/ l)1/2 . The corresponding column vectors ui have components that satisfy the following. (i) For λ = 0.3661,  3 8 − 3 0.3661 θ1 − 0.3661θ2 = 0 ⇒ u1 = (1 1.431)T . 2 (ii) For λ = 2.634, 3 8  − 3 2.634 θ1 − 2.634θ2 = 0 2 We can now construct P as



1 P= 1.431



u2 = (1

−2.097)T .

 1 −2.097

and define new variables (ξ, η) by (θ1 θ2 )T = P (ξ η)T . When the substitutions θ1 = ξ + η and θ2 = 1.431ξ −2.097η ≡ αξ − βη are made into the expressions for T and V , they both take on diagonal forms. This can be checked by computing the coefficients of ξ η in the two expressions. They are as follows. For V :

3 − αβ = 0,

and

for T :

4 16 + 2(α − β) − αβ = 0. 3 3

As an example, the full expression for the potential energy becomes V = Mg (2.524 ξ 2 + 3.699 η2 ). 1.47 Three particles each of mass m are attached to a light horizontal string having fixed ends, the string being thus divided into four equal portions, each of length a and under a tension T . Show that for small transverse vibrations the amplitudes xi of the normal modes satisfy Bx = (maω2 /T )x, where B is the matrix ⎛ ⎞ 2 −1 0 ⎝−1 2 −1⎠ . 0 −1 2 Estimate the lowest and highest eigenfrequencies using trial vectors (3 4 3)T and (3 − 4  T  T √ √ Use also the exact vectors 1 2 1 and 1 − 2 1 and compare the results.

3)T .

For the ith mass, with displacement yi , the force it experiences as a result of the tension in the string connecting it to the (i + 1)th mass is the resolved component of that tension yi+1 − yi T . Similarly the force due to the perpendicular to the equilibrium line, i.e. f = a

25

Matrices and vector spaces

yi−1 − yi T . Because the tension in the string connecting it to the (i − 1)th mass is f = a ends of the string are fixed the notional zeroth and fourth masses have y0 = y4 = 0. The equations of motion are, therefore, T [(0 − x1 ) + (x2 − x1 )], a T mx¨2 = [(x1 − x2 ) + (x3 − x2 )], a T mx¨3 = [(x2 − x3 ) + (0 − x3 )]. a

mx¨1 =

If the displacements are written as xi = Xi cos ωt and x = (X1 equations become

X2

X3 )T , then these

maω2 X1 = −2X1 + X2 , T maω2 X2 = X1 − 2X2 + X3 , − T maω2 X3 = X2 − 2X3 . − T −

This set of equations can be written as Bx = ⎛

2 B = ⎝−1 0

maω2 x, with T ⎞ −1 0 2 −1⎠ . −1 2

The Rayleigh–Ritz method shows that any estimate λ of

xT Bx always lies between the xT x

lowest and highest possible values of maω2 /T . Using the suggested trial vectors gives the following estimates for λ. (i) For x = (3

4

3)T λ = [(3, 4, 3)B (3 = [(3, 4, 3) (2

3)T ]/34

4 2

2)T ]/34

= 20/34 = 0.588. (ii) For x = (3

−4

3)T λ = [(3, −4, 3)B (3 −4 3)T ]/34 = [(3, −4, 3) (10 −14

10)T ]/34

= 116/34 = 3.412. Using, instead, the exact vectors yields the exact values of λ as follows.

26

Matrices and vector spaces

(i) For the eigenvector corresponding to the lowest eigenvalue, x = (1,  √ √ λ = (1, 2, 1)B(1, 2, 1)T /4  √ √ √ √ = (1, 2, 1)(2 − 2, 2 2 − 2, 2 − 2)T /4 √ = 2 − 2 = 0.586.

√ 2, 1)T ,

√ (ii) For the eigenvector corresponding to the highest eigenvalue, x = (1, − 2, 1)T ,  √ √ λ = (1, − 2, 1)B(1, − 2, 1)T /4  √ √ √ √ = (1, − 2, 1)(2 + 2, −2 2 − 2, 2 + 2)T /4 √ = 2 + 2 = 3.414. As can be seen, the (crude) trial vectors give excellent approximations to the lowest and highest eigenfrequencies.

2

Vector calculus

2.1 Evaluate the integral





˙ 2 dt a(b˙ · a + b · a˙ ) + a˙ (b · a) − 2(˙a · a)b − b|a|

in which a˙ and b˙ are the derivatives of the real vectors a and b with respect to t.

In order to evaluate this integral, we need to group the terms in the integrand so that each is a part of the total derivative of a product of factors. Clearly, the first three terms are the derivative of a(b · a), i.e. d [ a(b · a) ] = a˙ (b · a) + a(b˙ · a) + a(b · a˙ ). dt Remembering that the scalar product is commutative, and that |a|2 = a · a, we also have d ˙ · a) + b(˙a · a) + b(a · a˙ ) [ b(a · a) ] = b(a dt ˙ · a) + 2b(˙a · a). = b(a Hence,  d d [ a(b · a) ] − [ b(a · a) ] dt I = dt dt = a(b · a) − b(a · a) + h  

= a × (a × b) + h, where h is the (vector) constant of integration. To obtain the final line above, we used a special case of the expansion of a vector triple product. 2.3 The general equation of motion of a (non-relativistic) particle of mass m and charge q when it is placed in a region where there is a magnetic field B and an electric field E is m¨r = q(E + r˙ × B); here r is the position of the particle at time t and r˙ = dr/dt, etc. Write this as three separate equations in terms of the Cartesian components of the vectors involved. For the simple case of crossed uniform fields E = Ei, B = Bj, in which the particle starts from the origin at t = 0 with r˙ = v0 k, find the equations of motion and show the following:

27

28

Vector calculus (a) if v0 = E/B then the particle continues its initial motion; (b) if v0 = 0 then the particle follows the space curve given in terms of the parameter ξ by x=

mE (1 − cos ξ ), B 2q

y = 0,

z=

mE (ξ − sin ξ ). B 2q

Interpret this curve geometrically and relate ξ to t. Show that the total distance traveled by the particle after time t is given by    Bqt  2E t  sin dt . B 0  2m 

Expressed in Cartesian coordinates, the components of the vector equation read ˙ z − z˙ By ), mx¨ = qEx + q(yB ˙ z ), my¨ = qEy + q(˙zBx − xB ˙ y − yB ˙ x ). m¨z = qEz + q(xB For Ex = E, By = B and all other field components zero, the equations reduce to mx¨ = qE − qB z˙ ,

my¨ = 0,

˙ m¨z = qB x.

˙ The second of these, together with the initial conditions y(0) = y(0) = 0, implies that y(t) = 0 for all t. The final equation can be integrated directly to give m˙z = qBx + mv0 ,

(∗)

which can now be substituted into the first to give a differential equation for x:   qB mx¨ = qE − qB x + v0 , m   q qB 2 x = (E − v0 B). ⇒ x¨ + m m (i) If v0 = E/B then the equation for x is that of simple harmonic motion and x(t) = A cos ωt + B sin ωt, ˙ where ω = qB/m. However, in the present case, the initial conditions x(0) = x(0) =0 imply that x(t) = 0 for all t. Thus, there is no motion in either the x- or the y-direction and, as is then shown by (∗), the particle continues with its initial speed v0 in the z-direction. (ii) If v0 = 0, the equation of motion is x¨ + ω2 x =

qE , m

which again has sinusoidal solutions but has a non-zero RHS. The full solution consists of the same complementary function as in part (i) together with the simplest possible particular integral, namely x = qE/mω2 . It is therefore x(t) = A cos ωt + B sin ωt +

qE . mω2

29

Vector calculus

˙ The initial condition x(0) = 0 implies that A = −qE/(mω2 ), whilst x(0) = 0 requires that B = 0. Thus, qE (1 − cos ωt), mω2 qE qB qE (1 − cos ωt) = z˙ = x=ω (1 − cos ωt). 2 m mω mω

x= ⇒

Since z(0) = 0, straightforward integration gives   sin ωt qE qE t− = (ωt − sin ωt). z= mω ω mω2 Thus, since qE/mω2 = mE/B 2 q, the path is of the given parametric form with ξ = ωt. It is a cycloid in the plane y = 0; the x-coordinate varies in the restricted range 0 ≤ x ≤ 2qE/(mω2 ), whilst the z-coordinate continually increases, though not at a uniform rate. The element of path length is given by ds 2 = dx 2 + dy 2 + dz2 . In this case, writing qE/(mω) = E/B as μ,    2 1/2 dz dx 2 + dt ds = dt dt  1/2 = μ2 sin2 ωt + μ2 (1 − cos ωt)2 dt 1/2  2 dt = 2μ| sin 12 ωt| dt. = 2μ (1 − cos ωt) Thus the total distance traveled after time t is given by   t   2E t  qBt  1 s= 2μ| sin 2 ωt | dt = sin dt . B 0  2m  0 2.5 If two systems of coordinates with a common origin O are rotating with respect to each other, the measured accelerations differ in the two systems. Denoting by r and r position vectors in frames OXYZ and OX Y Z , respectively, the connection between the two is r¨ = r¨ + ω˙ × r + 2ω × r˙ + ω × (ω × r), where ω is the angular velocity vector of the rotation of OXYZ with respect to OX Y Z (taken as fixed). The third term on the RHS is known as the Coriolis acceleration, whilst the final term gives rise to a centrifugal force. Consider the application of this result to the firing of a shell of mass m from a stationary ship on the steadily rotating earth, working to the first order in ω (= 7.3 × 10−5 rad s−1 ). If the shell is fired with velocity v at time t = 0 and only reaches a height that is small compared with the radius of the earth, show that its acceleration, as recorded on the ship, is given approximately by r¨ = g − 2ω × (v + gt), where mg is the weight of the shell measured on the ship’s deck. The shell is fired at another stationary ship (a distance s away) and v is such that the shell would have hit its target had there been no Coriolis effect.

30

Vector calculus (a) Show that without the Coriolis effect the time of flight of the shell would have been τ = −2g · v/g 2 . (b) Show further that when the shell actually hits the sea it is off-target by approximately 2τ 1 [ (g × ω) · v ](gτ + v) − (ω × v)τ 2 − (ω × g)τ 3 . g2 3 (c) Estimate the order of magnitude  of this miss for a shell for which the initial speed v is 300 m s−1 , firing close to its maximum range (v makes an angle of π/4 with the vertical) in a northerly direction, whilst the ship is stationed at latitude 45◦ North.

As the earth is rotating steadily ω˙ = 0, and for the mass at rest on the deck, m¨r = mg + 0 + 2ω × 0˙ + mω × (ω × r). This, including the centrifugal effect, defines g which is assumed constant throughout the trajectory. For the moving mass (¨r is unchanged), mg + ω × (ω × r) = m¨r + 2mω × r˙ + mω × (ω × r), r¨ = g − 2ω × r˙ .

i.e.

Now, ωr˙  g and so to zeroth order in ω r¨ = g



r˙ = gt + v.

Resubstituting this into the Coriolis term gives, to first order in ω, r¨ = g − 2ω × (v + gt). (a) With no Coriolis force, r˙ = gt + v

and r = 12 gt 2 + vt.

Let s = 12 gτ 2 + vτ and use the observation that s · g = 0, giving 1 2 2 g τ 2

+ v · gτ = 0



τ =−

2v · g . g2

(b) With Coriolis force, r¨ = g − 2(ω × g)t − 2(ω × v), r˙ = gt − (ω × g)t 2 − 2(ω × v)t + v, r = 12 gt 2 − 13 (ω × g)t 3 − (ω × v)t 2 + vt.

(∗)

If the shell hits the sea at time T in the position r = s + , then (s + ) · g = 0, i.e. 0 = (s + ) · g = 12 g 2 T 2 − 0 − (ω × v) · g T 2 + v · g T , ⇒

−v · g = T ( 12 g 2 − (ω × v) · g),  −1 v·g (ω × v) · g ⇒ T =− 1 2 1− 1 2 g g 2 2   2(ω × v) · g ≈τ 1+ + ··· . g2

31

Vector calculus

Working to first order in ω, we may put T = τ in those terms in (∗) that involve another factor ω, namely ω × v and ω × g. We then find, to this order, that   1 4(ω × v) · g 2 1 s +  = g τ2 + τ + · · · − (ω × g)τ 3 2 g2 3 (ω × v) · g − (ω × v)τ 2 + vτ + 2 vτ g2 1 (ω × v) · g (2gτ 2 + 2vτ ) − (ω × g)τ 3 − (ω × v)τ 2 . =s+ g2 3 Hence, as stated in the question, =

1 2τ [ (g × ω) · v ](gτ + v) − (ω × v)τ 2 − (ω × g)τ 3 . 2 g 3

(c) With the ship at latitude 45◦ and firing the shell at close to 45◦ to the local horizontal, v and ω are almost parallel and the ω × v term can be set to zero. Further, with v in a northerly direction, (g × ω) · v = 0. Thus we are left with only the cubic term in τ . In this, τ=

2 × 300 cos(π/4) = 43.3 s, 9.8

and ω × g is in a westerly direction (recall that ω is directed northwards and g is directed downwards, towards the origin) and of magnitude 7 10−5 × 9.8 × sin(π/4) = 4.85 10−4 m s−3 . Thus the miss is by approximately − 13 × 4.85 10−4 × (43.3)3 = −13 m, i.e. some 10–15 m to the East of its intended target. 2.7 Parameterizing the hyperboloid x2 y2 z2 + 2 − 2 =1 2 a b c by x = a cos θ sec φ, y = b sin θ sec φ, z = c tan φ, show that an area element on its surface is    1/2 dS = sec2 φ c2 sec2 φ b2 cos2 θ + a 2 sin2 θ + a 2 b2 tan2 φ dθ dφ. Use this formula to show that the area of the curved surface x 2 + y 2 − z2 = a 2 between the planes z = 0 and z = 2a is   √ 1 πa 2 6 + √ sinh−1 2 2 . 2

With x = a cos θ sec φ, y = b sin θ sec φ and z = c tan φ, the tangent vectors to the surface are given in Cartesian coordinates by dr = (−a sin θ sec φ, b cos θ sec φ, 0), dθ dr = (a cos θ sec φ tan φ, b sin θ sec φ tan φ, c sec2 φ), dφ

32

Vector calculus

and the element of area by    dr dr   × dθ dφ dS =  dθ dφ    =  (bc cos θ sec3 φ, ac sin θ sec3 φ, −ab sec2 φ tan φ)  dθ dφ    1/2 dθ dφ. = sec2 φ c2 sec2 φ b2 cos2 θ + a 2 sin2 θ + a 2 b2 tan2 φ We set b = c = a and note that the plane z = 2a corresponds to φ = tan−1 2. The ranges of integration are therefore 0 ≤ θ < 2π and 0 ≤ φ ≤ tan−1 2, whilst dS = sec2 φ(a 4 sec2 φ + a 4 tan2 φ)1/2 dθ dφ, i.e. it is independent of θ. √ To evaluate the integral of dS, we set tan φ = sinh ψ/ 2, with 1 sec2 φ dφ = √ cosh ψ dψ 2

and

sec2 φ = 1 + 12 sinh2 ψ.

√ The upper limit for ψ will be given by  = sinh−1 2 2; we note that cosh  = 3. Integrating over θ and making the above substitutions yields  1/2 1 1 1 2 2 2 S = 2π √ cosh ψ dψ a 1 + sinh ψ + sinh ψ 2 2 2 0   √ = 2πa 2 cosh2 ψ dψ 0 √  2πa 2  = (cosh 2ψ + 1) dψ 2 0   √ 2πa 2 sinh 2ψ +ψ = 2 2 0 2 πa = √ [sinh ψ cosh ψ + ψ] 0 2   √ √ 1 πa 2 √ = √ [ (2 2)(3) + sinh−1 2 2 ] = πa 2 6 + √ sinh−1 2 2 . 2 2 



2.9 Verify by direct calculation that ∇ · (a × b) = b · (∇ × a) − a · (∇ × b).

The proof of this standard result for the divergence of a vector product is most easily carried out in Cartesian coordinates though, of course, the result is valid in any three-dimensional

33

Vector calculus

coordinate system. LHS = ∇ · (a × b) ∂ ∂ ∂ = (ay bz − az by ) + (az bx − ax bz ) + (ax by − ay bx ) ∂x ∂y ∂z       ∂by ∂by ∂bx ∂bx ∂bz ∂bz + ay + az − + − + = ax − ∂y ∂z ∂x ∂z ∂x ∂y       ∂ay ∂ay ∂ax ∂ax ∂az ∂az + bx − + by − + + bz − ∂y ∂z ∂x ∂z ∂x ∂y = −a · (∇ × b) + b · (∇ × a) = RHS.

2.11 Evaluate the Laplacian of the function ψ(x, y, z) =

zx 2 x 2 + y 2 + z2

(a) directly in Cartesian coordinates, and (b) after changing to a spherical polar coordinate system. Verify that, as they must, the two methods give the same result.

(a) In Cartesian coordinates we need to evaluate ∇ 2ψ =

∂ 2ψ ∂ 2ψ ∂ 2ψ + + 2. 2 2 ∂x ∂y ∂z

The required derivatives are ∂ψ 2xz(y 2 + z2 ) = 2 , ∂x (x + y 2 + z2 )2

∂ 2ψ (y 2 + z2 )(2zy 2 + 2z3 − 6x 2 z) = , ∂x 2 (x 2 + y 2 + z2 )3

∂ψ −2x 2 yz , = 2 ∂y (x + y 2 + z2 )2

∂ 2ψ 2zx 2 (x 2 + z2 − 3y 2 ) = − , ∂y 2 (x 2 + y 2 + z2 )3

∂ψ x 2 (x 2 + y 2 − z2 ) = , ∂z (x 2 + y 2 + z2 )2

∂ 2ψ 2zx 2 (3x 2 + 3y 2 − z2 ) =− . 2 ∂z (x 2 + y 2 + z2 )3

Thus, writing r 2 = x 2 + y 2 + z2 , 2z[ (y 2 + z2 )(y 2 + z2 − 3x 2 ) − 4x 4 ] (x 2 + y 2 + z2 )3 2z[ (r 2 − x 2 )(r 2 − 4x 2 ) − 4x 4 ] = r6 2z(r 2 − 5x 2 ) = . r4

∇ 2ψ =

(b) In spherical polar coordinates, ψ(r, θ, φ) =

r cos θ r 2 sin2 θ cos2 φ = r cos θ sin2 θ cos2 φ. r2

34

Vector calculus

The three contributions to ∇ 2 ψ in spherical polars are   ∂ψ 1 ∂ r2 (∇ 2 ψ)r = 2 r ∂r ∂r 2 = cos θ sin2 θ cos2 φ, r   ∂ ∂ψ 1 2 sin θ (∇ ψ)θ = 2 r sin θ ∂θ ∂θ   1 cos2 φ ∂ ∂ = sin θ (cos θ sin2 θ) r sin θ ∂θ ∂θ 2 cos φ (4 cos3 θ − 8 sin2 θ cos θ), = r ∂ 2ψ 1 (∇ 2 ψ)φ = 2 2 r sin θ ∂φ 2 cos θ = (−2 cos2 φ + 2 sin2 φ). r Thus, the full Laplacian in spherical polar coordinates reads cos θ (2 sin2 θ cos2 φ + 4 cos2 θ cos2 φ r − 8 sin2 θ cos2 φ − 2 cos2 φ + 2 sin2 φ) cos θ (4 cos2 φ − 10 sin2 θ cos2 φ − 2 cos2 φ + 2 sin2 φ) = r cos θ (2 − 10 sin2 θ cos2 φ) = r 2r cos θ(r 2 − 5r 2 sin2 θ cos2 φ) = . r4

∇ 2ψ =

Rewriting this last expression in terms of Cartesian coordinates, one finally obtains ∇ 2ψ =

2z(r 2 − 5x 2 ) , r4

which establishes the equivalence of the two approaches. 2.13 The (Maxwell) relationship between a time-independent magnetic field B and the current density J (measured in SI units in A m−2 ) producing it, ∇ × B = μ0 J, can be applied to a long cylinder of conducting ionized gas which, in cylindrical polar coordinates, occupies the region ρ < a. (a) Show that a uniform current density (0, C, 0) and a magnetic field (0, 0, B), with B constant (= B0 ) for ρ > a and B = B(ρ) for ρ < a, are consistent with this equation. Given that B(0) = 0 and that B is continuous at ρ = a, obtain expressions for C and B(ρ) in terms of B0 and a.

35

Vector calculus (b) The magnetic field can be expressed as B = ∇ × A, where A is known as the vector potential. Show that a suitable A can be found which has only one non-vanishing component, Aφ (ρ), and obtain explicit expressions for Aφ (ρ) for both ρ < a and ρ > a. Like B, the vector potential is continuous at ρ = a. (c) The gas pressure p(ρ) satisfies the hydrostatic equation ∇p = J × B and vanishes at the outer wall of the cylinder. Find a general expression for p.

(a) In cylindrical polars with B = (0, 0, B(ρ)), for ρ ≤ a we have   ∂B 1 ∂B , − , 0 . μ0 (0, C, 0) = ∇ × B = ρ ∂φ ∂ρ As expected, ∂B/∂φ = 0. The azimuthal component of the equation gives −

∂B = μ0 C ∂ρ

for

ρ≤a



B(ρ) = B(0) − μ0 Cρ.

Since B has to be differentiable at the origin of ρ and have no φ-dependence, B(0) must be zero. This, together with B = B0 for ρ > a requires that C = −B0 /(aμ0 ) and B(ρ) = B0 ρ/a for 0 ≤ ρ ≤ a. (b) With B = ∇ × A, consider A of the form A = (0, A(ρ), 0). Then   ∂ 1 ∂ (ρA), 0, (ρA) (0, 0, B(ρ)) = ρ ∂z ∂ρ   1 ∂ = 0, 0, (ρA) . ρ ∂ρ We now equate the only non-vanishing component on each side of the above equation, treating inside and outside the cylinder separately. For 0 < ρ ≤ a, B0 ρ 1 ∂ (ρA) = , ρ ∂ρ a B0 ρ 3 ρA = + D, 3a D B0 ρ 2 + . A(ρ) = 3a ρ Since A(0) must be finite (so that A is differentiable there), D = 0. For ρ > a, 1 ∂ (ρA) = B0 , ρ ∂ρ B0 ρ 2 + E, ρA = 2 E 1 A(ρ) = B0 ρ + . 2 ρ

36

Vector calculus

At ρ = a, the continuity of A requires B0 a 2 E 1 B0 a 2 = B0 a + ⇒ E = − . 3a 2 a 6 Thus, to summarize, B0 ρ 2 for 0 ≤ ρ ≤ a, 3a   ρ a2 − for ρ ≥ a. A(ρ) = B0 2 6ρ A(ρ) =

and

(c) For the gas pressure p (ρ) in the region 0 < ρ ≤ a, we have ∇p = J × B. In component form,       B0 ρ B0 dp , 0 × 0, 0, , 0, 0 = 0, − , dρ aμ0 a with p (a) = 0. B 2ρ dp =− 0 2 dρ μ0 a



B2 p (ρ) = 0 2μ0

 1−

 ρ 2  a

.

2.15 Maxwell’s equations for electromagnetism in free space (i.e. in the absence of charges, currents and dielectric or magnetic media) can be written (i) ∇ · B = 0,

(ii) ∇ · E = 0, 1 ∂E ∂B = 0, (iv) ∇ × B − 2 = 0. (iii) ∇ × E + ∂t c ∂t A vector A is defined by B = ∇ × A, and a scalar φ by E = −∇φ − ∂A/∂t. Show that if the condition 1 ∂φ (v) ∇ · A + 2 =0 c ∂t is imposed (this is known as choosing the Lorentz gauge), then A and φ satisfy wave equations as follows. 1 ∂ 2φ = 0, c2 ∂t 2 1 ∂ 2A (vii) ∇ 2 A − 2 2 = 0. c ∂t The reader is invited to proceed as follows. (vi) ∇ 2 φ −

(a) Verify that the expressions for B and E in terms of A and φ are consistent with (i) and (iii). (b) Substitute for E in (ii) and use the derivative with respect to time of (v) to eliminate A from the resulting expression. Hence obtain (vi). (c) Substitute for B and E in (iv) in terms of A and φ. Then use the gradient of (v) to simplify the resulting equation and so obtain (vii).

(a) Substituting for B in (i), ∇ · B = ∇ · (∇ × A) = 0,

as it is for any vector A.

37

Vector calculus

Substituting for E and B in (iii), ∂B ∂A ∂ ∇ ×E+ = −(∇ × ∇φ) − ∇ × + (∇ × A) = 0. ∂t ∂t ∂t Here we have used the facts that ∇ × ∇φ = 0 for any scalar, and that, since ∂/∂t and ∇ act on different variables, the order in which they are applied to A can be reversed. Thus (i) and (iii) are automatically satisfied if E and B are represented in terms of A and φ. (b) Substituting for E in (ii) and taking the time derivative of (v), ∂ (∇ · A), 0 = ∇ · E = −∇ 2 φ − ∂t 1 ∂ 2φ ∂ (∇ · A) + 2 2 . 0= ∂t c ∂t Adding these equations gives 0 = −∇ 2 φ +

1 ∂ 2φ . c2 ∂t 2

This is result (vi), the wave equation for φ. (c) Substituting for B and E in (iv) and taking the gradient of (v),   ∂ 1 ∂ 2A ∇ × (∇ × A) − 2 − ∇φ − 2 = 0, c ∂t ∂t 1 ∂ 1 ∂ 2A ∇(∇ · A) − ∇ 2 A + 2 (∇φ) + 2 2 = 0. c ∂t c ∂t 1 ∂ From (v), ∇(∇ · A) + 2 (∇φ) = 0. c ∂t 1 ∂ 2A = 0. c2 ∂t 2 In the second line we have used the vector identity − ∇ 2A +

Subtracting these gives

∇ 2 F = ∇(∇ · F) − ∇ × (∇ × F) to replace ∇ × (∇ × A). The final equation is result (vii). 2.17 Paraboloidal coordinates u, v, φ are defined in terms of Cartesian coordinates by x = uv cos φ,

y = uv sin φ,

z = 12 (u2 − v 2 ).

Identify the coordinate surfaces in the u, v, φ system. Verify that each coordinate surface (u = constant, say) intersects every coordinate surface on which one of the other two coordinates (v, say) is constant. Show further that the system of coordinates is an orthogonal one and determine its scale factors. Prove that the u-component of ∇ × a is given by   1 aφ ∂aφ 1 ∂av + − . (u2 + v 2 )1/2 v ∂v uv ∂φ

To find a surface of constant u we eliminate v from the given relationships: x 2 + y 2 = u2 v 2



2z = u2 −

x2 + y2 . u2

38

Vector calculus

This is an inverted paraboloid of revolution about the z-axis. The range of z is −∞ < z ≤ 12 u2 . Similarly, the surface of constant v is given by 2z =

x2 + y2 − v2. v2

This is also a paraboloid of revolution about the z-axis, but this time it is not inverted. The range of z is − 12 v 2 ≤ z < ∞. Since every constant-u paraboloid has some part of its surface in the region z > 0 and every constant-v paraboloid has some part of its surface in the region z < 0, it follows that every member of the first set intersects each member of the second, and vice versa. The surfaces of constant φ, y = x tan φ, are clearly (half-) planes containing the z-axis; each cuts the members of the other two sets in parabolic lines. We now determine (the Cartesian components of) the tangential vectors and test their orthogonality: ∂r = (v cos φ, v sin φ, u), ∂u ∂r = (u cos φ, u sin φ, −v), e2 = ∂v ∂r e3 = = (−uv sin φ, uv cos φ, 0), ∂φ e1 · e2 = uv(cos φ cos φ + sin φ sin φ) − uv = 0, e1 =

e2 · e3 = u2 v(− cos φ sin φ + sin φ cos φ) = 0, e1 · e3 = uv 2 (− cos φ sin φ + sin φ cos φ) = 0. This shows that all pairs of tangential vectors are orthogonal and therefore that the coordinate system is an orthogonal one. Its scale factors are given by the magnitudes of these tangential vectors: h2u = |e1 |2 = (v cos φ)2 + (v sin φ)2 + u2 = u2 + v 2 , h2v = |e2 |2 = (u cos φ)2 + (u sin φ)2 + v 2 = u2 + v 2 , h2φ = |e3 |2 = (uv sin φ)2 + (uv cos φ)2 = u2 v 2 . Thus hu = hv =

 u2 + v 2 ,

hφ = uv.

The u-component of ∇ × a is given by   ∂ hu ∂ (hφ aφ ) − (hv av ) [∇ × a ]u = hu hv hφ ∂v ∂φ   ∂  2 1 ∂ (uvaφ ) − ( u + v 2 av ) = √ ∂φ uv u2 + v 2 ∂v   aφ 1 ∂aφ 1 ∂av = √ + − , 2 2 v ∂v uv ∂φ u +v as stated in the question.

39

Vector calculus 2.19 Hyperbolic coordinates u, v, φ are defined in terms of Cartesian coordinates by x = cosh u cos v cos φ,

y = cosh u cos v sin φ,

z = sinh u sin v.

Sketch the coordinate curves in the φ = 0 plane, showing that far from the origin they become concentric circles and radial lines. In particular, identify the curves u = 0, v = 0, v = π/2 and v = π. Calculate the tangent vectors at a general point, show that they are mutually orthogonal and deduce that the appropriate scale factors are hu = hv = (cosh2 u − cos2 v)1/2 ,

hφ = cosh u cos v.

Find the most general function ψ(u) of u only that satisfies Laplace’s equation ∇ 2 ψ = 0.

In the plane φ = 0, i.e. y = 0, the curves u = constant have x and z connected by x2 z2 + = 1. cosh2 u sinh2 u This general form is that of an ellipse, with foci at (±1, 0). With u = 0, it is the line joining the two foci (covered twice). As u → ∞, and cosh u ≈ sinh u the form becomes that of a circle of very large radius. The curves v = constant are expressed by z2 x2 − = 1. cos2 v sin2 v These curves are hyperbolae that, for large x and z and fixed v, approximate z = ±x tan v, i.e. radial lines. The curve v = 0 is the part of the x-axis 1 ≤ x ≤ ∞ (covered twice), whilst the curve v = π is its reflection in the z-axis. The curve v = π/2 is the z-axis. In Cartesian coordinates a general point and its derivatives with respect to u, v and φ are given by r = cosh u cos v cos φ i + cosh u cos v sin φ j + sinh u sin v k, ∂r = sinh u cos v cos φ i + sinh u cos v sin φ j + cosh u sin v k, e1 = ∂u ∂r = − cosh u sin v cos φ i − cosh u sin v sin φ j + sinh u cos v k, e2 = ∂v ∂r e3 = = cosh u cos v(− sin φ i + cos φ j). ∂φ Now consider the scalar products: e1 · e2 = sinh u cos v cosh u sin v(− cos2 φ − sin2 φ + 1) = 0, e1 · e3 = sinh u cos2 v cosh u(− sin φ cos φ + sin φ cos φ) = 0, e2 · e3 = cosh2 u sin v cos v(sin φ cos φ − sin φ cos φ) = 0. As each is zero, the system is an orthogonal one.

40

Vector calculus

The scale factors are given by |ei | and are thus found from: |e1 |2 = sinh2 u cos2 v(cos2 φ + sin2 φ) + cosh2 u sin2 v = (cosh2 u − 1) cos2 v + cosh2 u(1 − cos2 v) = cosh2 u − cos2 v; |e2 |2 = cosh2 u sin2 v(cos2 φ + sin2 φ) + sinh2 u cos2 v = cosh2 u(1 − cos2 v) + (cosh2 u − 1) cos2 v = cosh2 u − cos2 v; |e3 |2 = cosh2 u cos2 v(sin2 φ + cos2 φ) = cosh2 u cos2 v. The immediate deduction is that hu = hv = (cosh2 u − cos2 v)1/2 ,

hφ = cosh u cos v.

An alternative form for hu and hv is (sinh2 u + sin2 v)1/2 . If a solution of Laplace’s equation is to be a function, ψ(u), of u only, then all differentiation with respect to v and φ can be ignored. The expression for ∇ 2 ψ reduces to    ∂ 1 hv hφ ∂ψ ∇ 2ψ = hu hv hφ ∂u hu ∂u    ∂ ∂ψ 1 cosh u cos v . = ∂u cosh u cos v(cosh2 u − cos2 v) ∂u Laplace’s equation itself is even simpler and reduces to   ∂ ∂ψ cosh u = 0. ∂u ∂u This can be rewritten as k 2k ∂ψ 2keu = = u , = ∂u cosh u e + e−u e2u + 1 dψ =

Aeu du 1 + (eu )2



ψ = B tan−1 eu + c.

This is the most general function of u only that satisfies Laplace’s equation.

3

Line, surface and volume integrals

3.1 The vector field F is defined by F = 2xzi + 2yz2 j + (x 2 + 2y 2 z − 1)k. Calculate ∇ × F and deduce that F can be written F = ∇φ. Determine the form of φ.

With F as given, we calculate the curl of F to see whether or not it is the zero vector: ∇ × F = (4yz − 4yz, 2x − 2x, 0 − 0) = 0. The fact that it is implies that F can be written as ∇φ for some scalar φ. The form of φ(x, y, z) is found by integrating, in turn, the components of F until consistency is achieved, i.e. until a φ is found that has partial derivatives equal to the corresponding components of F: ∂φ ∂x



φ(x, y, z) = x 2 z + g(y, z),

∂ [ x 2 z + g(y, z) ] ∂y



g(y, z) = y 2 z2 + h(z),

x 2 + 2y 2 z − 1 = Fz

=

∂ 2 [ x z + y 2 z2 + h(z) ] ∂z



h(z) = −z + k.

2xz = Fx = 2yz2 = Fy =

Hence, to within an unimportant constant, the form of φ is φ(x, y, z) = x 2 z + y 2 z2 − z.

3.3 A vector field F is given by F = xy 2 i + 2j + xk and L is a path parameterized by x = ct, y = c/t, z = d for the range 1 ≤ t ≤ 2. Evaluate the three integrals    (a) F dt, (b) F dy, (c) F · dr. L

L

L

Although all three integrals are along the same path L, they are not necessarily of the same type. The vector or scalar nature of the integral is determined by that of the integrand when it is expressed in a form containing the infinitesimal dt. (a) This is a vector integral and contains three separate integrations. We express each of the integrands in terms of t, according to the parameterization of the integration path 41

42

Line, surface and volume integrals

L, before integrating: 

 c3 i + 2 j + ct k dt F dt = t 1 L   1 2 2 3 = c ln t i + 2t j + ct k 2 1 3 = c3 ln 2 i + 2 j + c k. 2 

2



(b) This is a similar vector integral but here we must also replace the infinitesimal dy by the infinitesimal −c dt/t 2 before integrating:   c3 −c dt i + 2 j + ct k t t2 1  4 2 c 2c 2 = j − c i + ln t k 2t 2 t 1 4 3c i − c j − c2 ln 2 k. =− 8 



F dy = L

2



(c) This is a scalar integral and before integrating we must take the scalar product of F with dr = dx i + dy j + dz k to give a single integrand:  c c3 i + 2 j + ct k · (c i − 2 j + 0 k) dt t t 1   2 4 2c c − 2 dt = t t 1   2c 2 4 = c ln t + t 1 



F · dr = L

2



= c4 ln 2 − c.

3.5 Determine the point of intersection P , in the first quadrant, of the two ellipses x2 y2 x2 y2 + 2 = 1 and + 2 = 1. 2 2 a b b a Taking b < a, consider the contour L that bounds the area in the first quadrant that is common to the two ellipses. Show that the parts of L that lie along the coordinate axes contribute nothing to the line integral around L of x dy − y dx. Using a parameterization of each ellipse of the general form x = X cos φ and y = Y sin φ, evaluate the two remaining line integrals and hence find the total area common to the two ellipses. Note: The line integral of x dy − y dx around a general closed convex contour is equal to twice the area enclosed by that contour.

43

Line, surface and volume integrals

From the symmetry of the equations under the interchange of x and y, the point P must have x = y. Thus,   1 ab 1 2 x + 2 =1 ⇒ x= 2 . a2 b (a + b2 )1/2 Denoting as curve C1 the part of x2 y2 + 2 =1 a2 b that lies on the boundary of the common region, we parameterize it by x = a cos θ1 and y = b sin θ1 . Curve C1 starts from P and finishes on the y-axis. At P , a cos θ1 = x =

(a 2

ab + b2 )1/2



tan θ1 =

a . b

It follows that θ1 lies in the range tan−1 (a/b) ≤ θ1 ≤ π/2. Note that θ1 is not the angle between the x-axis and the line joining the origin O to the corresponding point on the curve; for example, when the point is P itself then θ1 = tan−1 a/b, whilst the line OP makes an angle of π/4 with the x-axis. Similarly, referring to that part of x2 y2 + 2 =1 b2 a that lies on the boundary of the common region as curve C2 , we parameterize it by x = b cos θ2 and y = a sin θ2 with 0 ≤ θ2 ≤ tan−1 (b/a). On the x-axis, both y and dy are zero and the integrand, x dy − y dx, vanishes. Similarly, the integrand vanishes at all points on the y-axis. Hence,  I = (x dy − y dx)  L (x dy − y dx) + (x dy − y dx) = C2

 =

0

+

C1

tan−1 (b/a)



[ ab(cos θ2 cos θ2 ) − ab sin θ2 (− sin θ2 ) ] dθ2

π/2 tan−1 (a/b)

[ ab(cos θ1 cos θ1 ) − ab sin θ1 (− sin θ1 ) ] dθ1

π b a + ab − tan−1 a 2 b b = 2ab tan−1 . a

= ab tan−1

As noted in the question, the area enclosed by L is equal to common area in all four quadrants is 4×

1 2

of this value, i.e. the total

1 b b × 2ab tan−1 = 4ab tan−1 . 2 a a

44

Line, surface and volume integrals

Note that if we let b → a then the two ellipses become identical circles and we recover the expected value of πa 2 for their common area. 3.7 Evaluate the line integral

 I=



y(4x 2 + y 2 ) dx + x(2x 2 + 3y 2 ) dy



C

around the ellipse x /a + y /b2 = 1. 2

2

2

As it stands this integral is complicated and, in fact, it is the sum of two integrals. The form of the integrand, containing powers of x and y that can be differentiated easily, makes this problem one to which Green’s theorem in a plane might usefully be applied. The theorem states that      ∂Q ∂P (P dx + Q dy) = − dx dy, ∂x ∂y C R where C is a closed contour enclosing the convex region R. In the notation used above, P (x, y) = y(4x 2 + y 2 ) and

Q(x, y) = x(2x 2 + 3y 2 ).

It follows that ∂P = 4x 2 + 3y 2 ∂y

and

∂Q = 6x 2 + 3y 2 , ∂x

leading to ∂Q ∂P − = 2x 2 . ∂x ∂y This can now be substituted into Green’s theorem and the y-integration carried out immediately as the integrand does not contain y. Hence,   I = 2x 2 dx dy R

 1/2 x2 2x 2b 1 − 2 dx = a −a  0 = 4b a 2 cos2 φ sin φ (−a sin φ dφ), on setting x = a cos φ, π  0 3 sin2 (2φ) dφ = 12 πba 3 . = −ba 

a

2

π

In the final line we have used the standard result for the integral of the square of a sinusoidal function.

45

Line, surface and volume integrals 3.9 A single-turn coil C of arbitrary shape is placed in a magnetic field B and carries a current I . Show that the couple acting upon the coil can be written as   B(r · dr). M = I (B · r) dr − I C

C

For a planar rectangular coil of sides 2a and 2b placed with its plane vertical and at an angle φ to a uniform horizontal field B, show that M is, as expected, 4abBI cos φ k.

For an arbitrarily shaped coil the total couple acting can only be found by considering that on an infinitesimal element and then integrating this over the whole coil. The force on an element dr of the coil is dF = I dr × B, and the moment of this force about the origin is dM = r × F. Thus the total moment is given by  r × (I dr × B) M= C   B(r · dr). = I (r · B) dr − I C

C

To obtain this second form we have used the vector identity a × (b × c) = (a · c)b − (a · b)c. To determine the couple acting on the rectangular coil we work in Cartesian coordinates with the z-axis vertical and choose the orientation of axes in the horizontal plane such that the edge of the rectangle of length 2a is in the x-direction. Then B = B cos φ i + B sin φ j. Considering the first term in M: (i) for the horizontal sides 

r = x i ± b k, dr = dx i, r · B = xB cos φ,  a   −a (r · B) dr = B cos φ i x dx + x dx = 0; −a

a

(ii) for the vertical sides 

r = ±a i + z k, dr = dz k, r · B = ±aB cos φ,   b  −b (+a) dz + (−a) dz = 4abB cos φ k. (r · B) dr = B cos φ k −b

b

For the second term in M, since the field is uniform it can be taken outside the integral as a (vector) constant. On the horizontal sides the remaining integral is   a r · dr = ± x dx = 0. −a

Similarly, the contribution from the vertical sides vanishes and the whole of the second term contributes nothing in this particular configuration. The total moment is thus 4abB cos φ k, as expected.

46

Line, surface and volume integrals 3.11 An axially symmetric solid body with its axis AB vertical is immersed in an incompressible fluid of density ρ0 . Use the following method to show that, whatever the shape of the body, for ρ = ρ(z) in cylindrical polars the Archimedean upthrust is, as expected, ρ0 gV , where V is the volume of the body.  Express the vertical component of the resultant force (− p dS, where p is the pressure) on the body in terms of an integral; note that p = −ρ0 gz and that for an annular surface element of width dl, n · nz dl = −dρ. Integrate by parts and use the fact that ρ(zA ) = ρ(zB ) = 0.

We measure z negatively from the water’s surface z = 0 so that the hydrostatic pressure is p = −ρ0 gz. By symmetry, there is no net horizontal force acting on the body. The upward force, F , is due to the net vertical component of the hydrostatic pressure acting upon the body’s surface:  F = −nˆ z · p dS  = −nˆ z · (−ρ0 gz)(2πρ nˆ dl), where 2πρ dl is the area of the strip of surface lying between z and z + dz and nˆ is the outward unit normal to that surface. Now, from geometry, nˆ z · nˆ is equal to minus the sine of the angle between dl and dz and so nˆ z · nˆ dl is equal to −dρ. Thus,  zB ρz(−dρ) F = 2πρ0 g zA   zB  ∂ρ z dz ρ = −2πρ0 g ∂z zA  2 zB  zB 2 ! ρ ρ dz . = −2πρ0 g z − 2 zA 2 zA But ρ(zA ) = ρ(zB ) = 0, and so the first contribution vanishes, leaving  zB F = ρ0 g πρ 2 dz = ρ0 gV , zA

where V is the volume of the solid. This is the mathematical form of Archimedes’ principle. Of course, the result is also valid for a closed body of arbitrary shape, ρ = ρ(z, φ), but a different method would be needed to prove it. 3.13 A vector field a is given by −zxr −3 i − zyr −3 j + (x 2 + y 2 )r −3 k, where r 2 = x 2 + y 2 + z2 . Establish that the field is conservative (a) by showing that ∇ × a = 0, and (b) by constructing its potential function φ.

We are told that a=−

zy x2 + y2 zx i − j + k, r3 r3 r3

47

Line, surface and volume integrals

with r 2 = x 2 + y 2 + z2 . We will need to differentiate r −3 with respect to x, y and z, using the chain rule, and so note that ∂r/∂x = x/r, etc. (a) Consider ∇ × a, term by term: [∇ × a]x = = = [∇ × a]y = = = [∇ × a]z = =

   2  ∂ ∂ x + y2 −zy − ∂y r3 ∂z r3 −3(x 2 + y 2 )y y 3(zy)z 2y + 3 + 3− 4 r4 r r r r r 3y (−x 2 − y 2 + x 2 + y 2 + z2 − z2 ) = 0; r5   2   ∂ −zx x + y2 ∂ − ∂z r3 ∂x r3 2x 3(x 2 + y 2 )x x 3(zx)z − 3− 3 + 4 r r r r r4 r 3x 2 (z − x 2 − y 2 − z2 + x 2 + y 2 ) = 0; r5     ∂ −zy −zx ∂ − ∂x r3 ∂y r3 3(zx)y 3(zy)x − 4 = 0. r4 r r r

Thus all three components of ∇ × a are zero, showing that a is a conservative field. (b) To construct its potential function we proceed as follows: ∂φ z −zx ⇒φ= 2 + f (y, z), = 2 2 2 3/2 2 ∂x (x + y + z ) (x + y + z2 )1/2 −zy ∂f ∂φ −zy = 2 + = 2 ⇒ f (y, z) = g(z), 2 2 3/2 2 2 3/2 ∂y (x + y + z ) (x + y + z ) ∂y x2 + y2 ∂φ = 2 ∂z (x + y 2 + z2 )3/2 1 −z z ∂g = 2 + 2 + (x + y 2 + z2 )1/2 (x + y 2 + z2 )3/2 ∂z ⇒ g(z) = c. Thus, φ(x, y, z) = c +

z z =c+ . (x 2 + y 2 + z2 )1/2 r

The very fact that we can construct a potential function φ = φ(x, y, z) whose derivatives are the components of the vector field shows that the field is conservative.

48

Line, surface and volume integrals 3.15 A force F(r) acts on a particle at r. In which of the following cases can F be represented in terms of a potential? Where it can, find the potential.   2  r 2(x − y) r exp − 2 ; (a) F = F0 i − j − 2 a   a 2  (x 2 + y 2 − a 2 ) r F0 zk + r exp − 2 ; (b) F = 2 a a a a(r × k) (c) F = F0 k + . r2

(a) We first write the field entirely in terms of the Cartesian unit vectors using r = x i + y j + z k and then attempt to construct a suitable potential function φ:  F = F0 =

  2 2(x − y) r i− j− r exp − 2 2 a a

F0  2 (a − 2x 2 + 2xy) i + (−a 2 − 2xy + 2y 2 ) j a2  2 r + (−2xz + 2yz) k exp − 2 . a

Since the partial derivative of exp(−r 2 /a 2 ) with respect to any Cartesian coordinate u is exp(−r 2 /a 2 )(−2r/a 2 )(u/r), the z-component of F appears to be the most straightforward to tackle first:  2 r ∂φ F0 = 2 (−2xz + 2yz) exp − 2 ∂z a a  2 r ⇒ φ(x, y, z) = F0 (x − y) exp − 2 + f (x, y) a ≡ φ1 (x, y, z) + f (x, y). Next we examine the derivatives of φ = φ1 + f with respect to x and y to see how closely they generate Fx and Fy :   2  2  r r −2x ∂φ1 = F0 exp − 2 + (x − y) exp − 2 ∂x a a a2 F0 = 2 (a 2 − 2x 2 + 2xy) exp(−r 2 /a 2 ) = Fx (as given), a   2  2  r r −2y ∂φ1 = F0 − exp − 2 + (x − y) exp − 2 and ∂y a a a2 F0 = 2 (−a 2 − 2xy + 2y 2 ) exp(−r 2 /a 2 ) = Fy (as given). a  2 r Thus, to within an arbitrary constant, φ1 (x, y, z) = F0 (x − y) exp − 2 is a suitable a potential function for the field, without the need for any additional function f (x, y).

49

Line, surface and volume integrals

(b) We follow the same line of argument as in part (a). First, expressing F in terms of i, j and k,   2  F0 r x 2 + y 2 − a2 F= r exp − 2 zk+ 2 a a a F0  2 = 3 x(x + y 2 − a 2 ) i + y(x 2 + y 2 − a 2 ) j a  2 r 2 2 + z(x + y ) k exp − 2 , a and then constructing a possible potential function φ. Again starting with the z-component:  2 r ∂φ F0 z 2 2 = 3 (x + y ) exp − 2 , ∂z a a  2 F0 2 r ⇒ φ(x, y, z) = − (x + y 2 ) exp − 2 + f (x, y) 2a a ≡ φ1 (x, y, z) + f (x, y).   2  r ∂φ1 F0 2x(x 2 + y 2 ) exp − 2 = Fx (as given), Then, =− 2x − ∂x 2a a2 a   2  r ∂φ1 F0 2y(x 2 + y 2 ) exp − 2 = Fy (as given). and =− 2y − 2 ∂y 2a a a  2 F0 2 r 2 Thus, φ1 (x, y, z) = (x + y ) exp − 2 , as it stands, is a suitable potential function 2a a for F(r) and establishes the conservative nature of the field. (c) Again we express F in Cartesian components:   ax a(r × k) ay F = F0 k + = 2 i − 2 j + k. 2 r r r That the z-component of F has no dependence on y whilst its y-component does depend upon z suggests that the x-component of ∇ × F may not be zero. To test this out we compute   ∂ −ax 2axz ∂(1) − (∇ × F)x = = 0 − 4 = 0, ∂y ∂z r2 r and find that it is not. To have even one component of ∇ × F non-zero is sufficient to show that F is not conservative and that no potential function can be found. There is no point in searching further! The same conclusion can be reached by considering the implication of Fz = k, namely that any possible potential function has to have the form φ(x, y, z) = z + f (x, y). However, ∂φ/∂x is known to be −ay/r 2 = −ay/(x 2 + y 2 + z2 ). This yields a contradiction, as it requires ∂f (x, y)/∂x to depend on z, which is clearly impossible.

50

Line, surface and volume integrals 3.17 The vector field f has components yi − xj + k and γ is a curve given parametrically by r = (a − c + c cos θ )i + (b + c sin θ )j + c2 θ k, 0 ≤ θ ≤ 2π.  Describe the shape of the path γ and show that the line integral γ f · dr vanishes. Does this result imply that f is a conservative field?

As θ increases from 0 to 2π, the x- and y-components of r vary sinusoidally and in quadrature about fixed values a − c and b. Both variations have amplitude c and both return to their initial values when θ = 2π. However, the z-component increases monotonically from 0 to a value of 2πc2 . The curve γ is therefore one loop of a circular spiral of radius c and pitch 2πc2 . Its axis is parallel to the z-axis and passes through the points (a − c, b, z). The line element dr has components (−c sin θ dθ, c cos θ dθ, c2 dθ) and so the line integral of f along γ is given by  2π   y(−c sin θ) − x(c cos θ) + c2 dθ f · dr = γ



0

=





−c(b + c sin θ) sin θ − c(a − c + c cos θ) cos θ + c2 dθ





0

 =

 −bc sin θ − c2 sin2 θ − c(a − c) cos θ − c2 cos2 θ + c2 dθ

0

= 0 − πc2 − 0 − πc2 + 2πc2 = 0. However, this does not imply that f is a conservative field since (i) γ is not a closed loop, and (ii) even if it were, the line integral has to vanish for every loop, not just for a particular one. Further, ∇ × f = (0 − 0, 0 − 0, −1 − 1) = (0, 0, −2) = 0, showing explicitly that f is not conservative.  3.19 Evaluate the surface integral r · dS, where r is the position vector, over that part of the surface z = a 2 − x 2 − y 2 for which z ≥ 0, by each of the following methods. (a) Parameterize the surface as x = a sin θ cos φ, y = a sin θ sin φ, z = a 2 cos2 θ , and show that r · dS = a 4 (2 sin3 θ cos θ + cos3 θ sin θ ) dθ dφ. (b) Apply the divergence theorem to the volume bounded by the surface and the plane z = 0.

(a) With x = a sin θ cos φ, y = a sin θ sin φ, z = a 2 cos2 θ, we first check that this does parameterize the surface appropriately: a 2 − x 2 − y 2 = a 2 − a 2 sin2 θ(cos2 φ + sin2 φ) = a 2 (1− sin2 θ) = a 2 cos2 θ = z. We see that it does so for the relevant part of the surface, i.e. that which lies above the plane z = 0 with 0 ≤ θ ≤ π/2. It would not do so for the part with z < 0 for which x 2 + y 2 has to be greater than a 2 ; this is not catered for by the given parameterization.

51

Line, surface and volume integrals

Having carried out this check, we calculate expressions for dS and hence r · dS in terms of θ and φ as follows: r = a sin θ cos φ i + a sin θ sin φ j + a 2 cos2 θ k, and the tangent vectors at the point (θ, φ) on the surface are given by ∂r = a cos θ cos φ i + a cos θ sin φ j − 2a 2 cos θ sin θ k, ∂θ ∂r = −a sin θ sin φ i + a sin θ cos φ j. ∂φ The corresponding vector element of surface area is thus ∂r ∂r × ∂θ ∂φ 3 = 2a cos θ sin2 θ cos φ i + 2a 3 cos θ sin2 θ sin φ j + a 2 cos θ sin θ k,

dS =

giving r · dS as r · dS = 2a 4 cos θ sin3 θ cos2 φ + 2a 4 cos θ sin3 θ sin2 φ + a 4 cos3 θ sin θ = 2a 4 cos θ sin3 θ + a 4 cos3 θ sin θ. This is to be integrated over the ranges 0 ≤ φ < 2π and 0 ≤ θ ≤ π/2 as follows: 

 r · dS = a 4





π/2

(2 sin3 θ cos θ + cos3 θ sin θ) dθ 0   0 π/2  π/2  sin4 θ − cos4 θ 4 + = 2πa 2 4 4 0 0   4 2 1 3πa = 2πa 4 + = . 4 4 2 dφ

 (b) The divergence of the vector field r is 3, a constant, and so the surface integral r · dS taken over the complete surface  (including the part that lies in the plane z = 0) is, by the divergence theorem, equal to three times the volume V of the region bounded by . Now, 

a2

V = 0



 πρ 2 dz = 0

a2

π(a 2 − z) dz = π(a 4 − 12 a 4 ) = 12 πa 4 ,

and so  r · dS = 3πa 4 /2. However, on the part of the surface lying in the plane z = 0, r = x i + y j + 0 k, whilst dS = −dS k. Consequently the scalar product r · dS = 0; in words, for any point on this face its position vector is orthogonal to the normal to the face. The surface integral over this face therefore contributes nothing to the total integral and the value obtained is that due to the curved surface alone, in agreement with the result in (a).

52

Line, surface and volume integrals 3.21 Use the result



 ∇φ dV = V

φ dS, S

together with an appropriately chosen scalar function φ, to prove that the position vector r¯ of the center of mass of an arbitrarily shaped body of volume V and uniform density can be written  1 1 2 ¯r = r dS. V S 2

The position vector of the center of mass is defined by   r¯ ρ dV = rρ dV . V

V

In order to make use of the given equation, we need to find a scalar function f that is such that ∇f = r; when this is substituted into the RHS of the above equation, the expression for r¯ can be transformed into a surface integral, rather than a volume integral. A suitable function for this purpose is f (r) = 12 r 2 . Writing r in this form and canceling the constant ρ, we have, using the given general result, that     1 2 1 2 r¯ V = ∇ r dS. r dV = 2 2 V S From this it follows immediately that r¯ =

1 V

 S

1 2 r 2

dS.

This result provides an alternative method of finding the center of mass z¯ k of the uniform hemisphere r = a, 0 ≤ θ ≤ π/2, 0 ≤ φ < 2π. The curved surface contributes 3a/4 to z¯ and the plane surface contributes −3a/8, giving z¯ = 3a/8. 3.23 Demonstrate the validity of the divergence theorem: (a) by calculating the flux of the vector F= through the spherical surface |r| = (b) by showing that

√ 3a;

(r 2

∇ ·F=

αr + a 2 )3/2

3αa 2 (r 2 + a 2 )5/2

and evaluating the volume integral of ∇ · F over the interior of the sphere |r| = substitution r = a tan θ will prove useful in carrying out the integration.

(a) The field is radial with F=

(r 2

αr αr = 2 eˆ r . 2 3/2 +a ) (r + a 2 )3/2

√ 3a. The

53

Line, surface and volume integrals

The total flux is therefore given by  √ √ 4πr 2 α r  4πa 3 α 3 3 3 3πα = 2 = = . (r + a 2 )3/2 r=a √3 8a 3 2 (b) From the divergence theorem, the total flux over the surface of the sphere is equal to the volume integral of its divergence within the sphere. The divergence is given by   1 ∂ 1 ∂ 2 r2 α r ∇ · F = 2 (r Fr ) = 2 r ∂r r ∂r (r 2 + a 2 )3/2   2 1 3αr 3αr 4 = 2 − 2 r (r 2 + a 2 )3/2 (r + a 2 )5/2 3αa 2 = 2 , (r + a 2 )5/2 and on integrating over the sphere, we have 



3αa 2 4πr 2 dr, set r = a tan θ, 0 ≤ θ ≤ π3 , 2 )5/2 + a 0  π/3 2 2 a tan θ a sec2 θ 2 dθ = 12παa a 5 sec5 θ 0  π/3 sin2 θ cos θ dθ = 12πα

∇ · F dV = V

√ 3a

(r 2

0



sin3 θ = 12πα 3

π/3 0



√ 3 3 3πα = 12πα = , 8 2

as in (a).

The equality of the results in parts (a) and (b) is in accordance with the divergence theorem. 3.25 In a uniform conducting medium with unit relative permittivity, charge density ρ, current density J, electric field E and magnetic field B, Maxwell’s electromagnetic equations take the form (with μ0 0 = c−2 ) (i) ∇ · B = 0, (ii) ∇ · E = ρ/ 0 , (iii) ∇ × E + B˙ = 0,

˙ 2 ) = μ0 J. (iv) ∇ × B − (E/c

2 The density of stored energy in the medium is given by 12 ( 0 E 2 + μ−1 0 B ). Show that the rate of change of the total stored energy in a volume V is equal to   1 J · E dV − (E × B) · dS, − μ0 S V

where S is the surface bounding V . [The first integral gives the ohmic heating loss, whilst the second gives the electromagnetic energy flux out of the bounding surface. The vector μ−1 0 (E × B) is known as the Poynting vector.]

54

Line, surface and volume integrals

The total stored energy is equal to the volume integral of the energy density. Let R be its rate of change. Then, differentiating under the integral sign, we have    d 0 2 1 2 E + R= B dV dt V 2 2μ0    1 ˙ ˙ = 0 E · E + B · B dV . μ0 V Now using (iv) and (iii), we have    1 2 2 0 E · (−μ0 c J + c ∇ × B) − B · (∇ × E) dV R= μ0 V     1 2 B · (∇ × E) dV 0 c E · (∇ × B) − = − E · J dV + μ0 V V  1 = − E · J dV − ∇ · (E × B) dV μ0 V V  1 = − E · J dV − (E × B) · dS, by the divergence theorem. μ0 S V To obtain the penultimate line we used the vector identity ∇ · (a × b) = b · (∇ × a) − a · (∇ × b).

3.27 The vector field F is given by F = (3x 2 yz + y 3 z + xe−x )i + (3xy 2 z + x 3 z + yex )j + (x 3 y + y 3 x + xy 2 z2 )k.  Calculate (a) directly, and (b) by using Stokes’ theorem the value of the line integral L F · dr, where L is the (three-dimensional) closed contour OABCDEO defined by the successive vertices (0, 0, 0), (1, 0, 0), (1, 0, 1), (1, 1, 1), (1, 1, 0), (0, 1, 0), (0, 0, 0).

(a) This calculation is a piece-wise evaluation of the line integral, made up of a series of scalar products of the length of a straight piece of the contour and the component of F parallel to it (integrated if that component varies along the particular straight section). On OA, y = z = 0 and Fx = xe−x ;  1  1  −x −x 1 xe dx = −xe 0 + e−x dx = 1 − 2e−1 . I1 = 0

0

On AB, x = 1 and y = 0 and Fz = 0; the integral I2 is zero. On BC, x = 1 and z = 1 and Fy = 3y 2 + 1 + ey;  1 I3 = (3y 2 + 1 + ey) dy = 1 + 1 + 12 e. 0

On CD, x = 1 and y = 1 and Fz = 1 + 1 + z2 ;  0 (1 + 1 + z2 ) dz = −1 − 1 − 13 . I4 = 1

55

Line, surface and volume integrals

On DE, y = 1 and z = 0 and Fx = xe−x ;  0 I5 = xe−x dx = −1 + 2e−1 . 1

On EO, x = z = 0 and Fy = ye ; 0



0

I6 = 1

ye0 dy = − 12 .

Adding up these six contributions shows that the complete line integral has the value e 5 − . 2 6 (b) As a simple sketch shows, the given contour is three-dimensional. However, it is equivalent to two plane square contours, one OADEO (denoted by S1 ) lying in the plane z = 0 and the other ABCDA (S2 ) lying in the plane x = 1; the latter is traversed in the negative sense. The common segment AD does not form part of the original contour but, as it is traversed in opposite senses in the two constituent contours, it (correctly) contributes nothing to the line integral. To use Stokes’ theorem we first need to calculate (∇ × F)x = x 3 + 3y 2 x + 2yxz2 − 3xy 2 − x 3 = 2yxz2 , (∇ × F)y = 3x 2 y + y 3 − 3x 2 y − y 3 − y 2 z2 = −y 2 z2 , (∇ × F)z = 3y 2 z + 3x 2 z + yex − 3x 2 z − 3y 2 z = yex . Now, S1 has its normal in the positive z-direction and so only the z-component of ∇ × F is needed in the first surface integral of Stokes’ theorem. Likewise only the x-component of ∇ × F is needed in the second integral, but its value must be subtracted because of the sense in which its contour is traversed:    (∇ × F) · dr = (∇ × F)z dx dy − (∇ × F)x dy dz OABCDEO

S1

S2

1

 =

1

 ye dx dy −

1



1

x

0

0

0

0

11 e 5 1 (e − 1) − 2 = − . 2 23 2 6 As they must, the two methods give the same value. =

2y × 1 × z2 dy dz

4

Fourier series

4.1 Prove the orthogonality relations that form the basis of the Fourier series representation of functions.

All of the results are based on the values of the integrals      x0 +L  x0 +L 2πnx 2πnx sin cos dx and C(n) = dx S(n) = L L x0 x0 for integer values of n. Since in all cases with n ≥ 1 the integrand goes through a whole number of complete cycles, the “area under the curve” is zero. For the case n = 0, the integrand in S(n) is zero and so therefore is S(0); for C(0) the integrand is unity and the value of C(0) is L. We now apply these observations to integrals whose integrands are the products of two sinusoidal functions with arguments that are multiples of a fundamental frequency. The integration interval is equal to the period of that fundamental frequency. To express the integrands in suitable forms, repeated use will be made of the expressions for the sums and differences of sinusoidal functions. We consider first the product of a sine function and a cosine function:      x0 +L 2πpx 2πrx cos sin I1 = L L x0     x0 +L   2π(r + p)x 2π(r − p)x 1 = sin + sin dx 2 L L x0 1 = [S(r + p) + S(r − p)] = 0, for all r and p. 2 Next, we consider the product of two cosines:      x0 +L 2πrx 2πpx I2 = cos cos L L x0     x0 +L   2π(r + p)x 2π(r − p)x 1 cos + cos dx = 2 L L x0 1 = [C(r + p) + C(r − p)] = 0, 2 unless r = p > 0 when I2 = 12 L. If r and p are both zero, then the integrand is unity and I2 = L. 56

57

Fourier series

Finally, for the product of two sine functions: 

x0 +L

I3 =

x0 x0 +L

 =

   2πpx 2πrx sin L L      2π(r − p)x 2π(r + p)x 1 cos − cos dx 2 L L 

sin

x0

1 = [C(r − p) − C(r + p)] = 0, 2 unless r = p > 0 when I3 = 12 L. If either of r and p is zero, then the integrand is zero and I3 = 0. In summary, all of the integrals have zero value except for those in which the integrand is the square of a single sinusoid. In these cases the integral has value 12 L for all integers r (= p) that are > 0. For r (= p) equal to zero, the sin2 integral has value zero and the cos2 integral has value L. 4.3 Which of the following functions of x could be represented by a Fourier series over the range indicated? (a) tanh−1 (x), (b) tan x, (c) | sin x |−1/2 , (d) cos−1 (sin 2x), (e) x sin(1/x),

−∞ < x < ∞; −∞ < x < ∞; −∞ < x < ∞; −∞ < x < ∞; −π −1 < x ≤ π −1 , cyclically repeated.

The Dirichlet conditions that a function must satisfy before it can be represented by a Fourier series are: (i) the function must be periodic; (ii) it must be single-valued and continuous, except possibly at a finite number of finite discontinuities; (iii) it must have only a finite number of maxima and minima within one period; (iv) the integral over one period of |f (x)| must converge. We now test the given functions against these: (a) tanh−1 (x) is not a periodic function, since it is only defined for −1 ≤ x ≤ 1 and changes (monotonically) from −∞ to +∞ as x varies over this restricted range. This function therefore fails condition (i) and cannot be represented as a Fourier series. (b) tan x is a periodic function but its discontinuities are not finite, nor is its absolute modulus integrable. It therefore fails tests (ii) and (iv) and cannot be represented as a Fourier series. (c) | sin x|−1/2 is a periodic function of period π and, although it becomes infinite at x = nπ, there are no infinite discontinuities. Near x = 0, say, it behaves as |x|−1/2 and its absolute modulus is therefore integrable. There is only one minimum in any one period. The function therefore satisfies all four Dirichlet conditions and can be represented as a Fourier series.

58

Fourier series

(d) cos−1 (sin 2x) is clearly a multi-valued function and fails condition (ii); it cannot be represented as a Fourier series. (e) x sin(1/x), for −π −1 < x ≤ π −1 (cyclically repeated) is clearly cyclic (by definition), continuous, bounded, single-valued and integrable. However, since sin(1/x) oscillates with unlimited frequency near x = 0, there are an infinite number of maxima and minima in any region enclosing x = 0. Condition (iii) is therefore not satisfied and the function cannot be represented as a Fourier series. 4.5 Find the Fourier series of the function f (x) = x in the range −π < x ≤ π. Hence show that 1−

π 1 1 1 + − + ··· = . 3 5 7 4

This is an odd function in x and so a sine series with period 2π is appropriate. The coefficient of sin nx will be given by  π 2 bn = x sin nx dx 2π −π    π cos nx 1 " x cos nx #π − dx + = π n n −π −π   π(−1)n − (−π)(−1)n 2(−1)n+1 1 − +0 = . = π n n

Thus,

x = f (x) = 2

∞  (−1)n+1 n=1

n

sin nx.

We note in passing that although this series is convergent, as it must be, it has poor (i.e. n−1 ) convergence; this can be put down to the periodic version of the function having a discontinuity (of 2π) at the end of each basic period. To obtain the sum of a series from such a Fourier representation, we must make a judicious choice for the value of x – making such a choice is rather more of an art than a science! Here, setting x = π/2 gives ∞  π (−1)n+1 sin(nπ/2) =2 2 n n=1

=2 ⇒

 (−1)n+1 (−1)(n−1)/2 ) , n n odd

π 1 1 1 1 = − + − + ··· . 4 1 3 5 7

59

Fourier series 4.7 For the function f (x) = 1 − x,

0 ≤ x ≤ 1,

a Fourier sine series can be found by continuing it in the range −1 < x ≤ 0 as f (x) = −1 − x. The function thus has a discontinuity of 2 at x = 0. The series is 1 − x = f (x) =

∞ 2  sin nπx . π n=1 n

(∗)

In order to obtain a cosine series, the continuation has to be f (x) = 1 + x in the range −1 < x ≤ 0. The function then has no discontinuity at x = 0 and the corresponding series is 4  cos nπx 1 . (∗∗) 1 − x = f (x) = + 2 2 π n odd n2 For these continued functions and series, consider (i) their derivatives and (ii) their integrals. Do they give meaningful equations? You will probably find it helpful to sketch all the functions involved.

(i) Derivatives (a) The sine series. With the continuation given, the derivative df/dx has the value −1 everywhere, except at the origin where the function is not defined (though f (0) = 0 seems the only possible choice), continuous or differentiable. Differentiating the given series (∗) for f (x) yields ∞  df =2 cos nπx. dx n=1

This series does not converge and the equation is not meaningful. (b) The cosine series. With the stated continuation for f (x) the derivative is +1 for −1 < x ≤ 0 and is −1 for 0 ≤ x ≤ 1. It is thus the negative of an odd (about x = 0) unit square-wave, whose Fourier series is 4  sin nπx . − π n odd n This is confirmed by differentiating (∗∗) term by term to obtain the same result: 4  −nπ sin nπx df 4  sin nπx = 2 . = − dx π n odd n2 π n odd n (ii) Integrals Since integrals contain an arbitrary constant of integration, we will define F (−1) = 0, where F (x) is the indefinite integral of f (x). (a) The sine series. For −1 ≤ x ≤ 0,  x Fa (x) = F (−1) + (−1 − x) dx = −x − 12 x 2 − 12 . −1

For 0 ≤ x ≤ 1,



Fa (x) = F (0) + 0

x

x  (1 − x) dx = − 12 + x − 12 x 2 0 = x − 12 x 2 − 12 .

60

Fourier series

This is a continuous function and, like all indefinite integrals, is “smoother” than the function from which it is derived; this latter property will be reflected in the improved convergence of the derived series. Integrating term by term we find that its Fourier series is given by 

∞ x 

sin nπx dx n −1 n=1  ∞  cos nπx x 2 − = π n=1 πn2 −1

2 Fa (x) = π

∞ 2  (−1)n − cos nπx = 2 π n=1 n2 ∞ 1 2  cos nπx =− − 2 , 6 π n=1 n2

 n −2 a series that has n−2 convergence. Here we have used the result that ∞ = n=1 (−1) n 2 −π /12. (b) The cosine series. The corresponding indefinite integral in this case is Fb (x) = x + 12 x 2 + Fb (x) = x −

1 2 x 2

+

1 2 1 2

for

− 1 ≤ x ≤ 0,

for

0 ≤ x ≤ 1,

and the corresponding integrated series, which has even better convergence (n−3 ), is given by 1 4  sin nπx . (x + 1) + 3 2 π n odd n3 However, to have a true Fourier series expression, we must substitute a Fourier series for the x/2 term that arises from integrating the constant ( 12 ) in (∗∗). This series must be that for x/2 across the complete range −1 ≤ x ≤ 1, and so neither (∗) nor (∗∗) can be rearranged for the purpose. A straightforward calculation (see Problem 4.25 part (b), if necessary) yields the poorly convergent sine series x=2

∞  (−1)n+1 n=1



sin nπx,

and makes the final expression for Fb (x) ∞ 4  sin nπx 1  (−1)n+1 + sin nπx + 3 . 2 n=1 nπ π n odd n3

As will be apparent from a simple sketch, the first series in the above expression dominates; all of its terms are present and it has only n−1 convergence. The second series has alternate terms missing and its convergence ∼ n−3 .

61

Fourier series 4.9 Find the Fourier coefficients in the expansion of f (x) = exp x over the range −1 < x < 1. What value will the expansion have when x = 2?

Since the Fourier series will have period 2, we can say immediately that at x = 2 the series will converge to the value it has at x = 0, namely 1. As the function f (x) = exp x is neither even nor odd, its Fourier series will contain both sine and cosine terms. The cosine coefficients are given by  2 1 x e cos(nπx) dx 2 −1  1  x 1 nπ sin(nπx) ex dx = cos(nπx) e −1 +

an =

−1



−1

= (−1) (e − e ) + nπ sin(nπx) ex  1 − n2 π 2 cos(nπx) ex dx n

1

1 −1

−1

= 2(−1)n sinh 1 − n2 π 2 an , ⇒

an =

2(−1)n sinh 1 . 1 + n2 π 2

Similarly, the sine coefficients are given by  2 1 x e sin(nπx) dx bn = 2 −1  1  1 = sin(nπx) ex −1 − nπ cos(nπx) ex dx −1



= 0 + −nπ

1 cos(nπx) ex −1





1

n2 π 2 sin(nπx) ex dx −1

= 2(−1)n+1 nπ sinh 1 − n2 π 2 bn , ⇒

bn =

2(−1)n+1 nπ sinh 1 . 1 + n2 π 2

4.11 Consider the function f (x) = exp(−x 2 ) in the range 0 ≤ x ≤ 1. Show how it should be continued to give as its Fourier series a series (the actual form is not wanted) (a) with only cosine terms, (b) with only sine terms, (c) with period 1 and (d) with period 2. Would there be any difference between the values of the last two series at (i) x = 0, (ii) x = 1?

The function and its four continuations are shown as (a)–(d) in Figure 4.1. Note that in the range 0 ≤ x ≤ 1, all four graphs are identical. Where a continued function has a discontinuity at the ends of its basic period, the series will yield a value at those end-points that is the average of the function’s values on the

62

Fourier series

0

1

0

(a)

1

0

1

0

2

4

(c)

(d) Figure 4.1 The continuations of exp(−x ) in 0 ≤ x ≤ 1 to give: (a) cosine terms only; (b) sine terms only; (c) period 1; (d) period 2. (b)

2

two sides of the discontinuity. Thus for continuation (c) both (i) x = 0 and (ii) x = 1 are end-points, and the value of the series there will be (1 + e−1 )/2. For continuation (d), x = 0 is an end-point, and the series will have value 12 (1 + e−4 ). However, x = 1 is not a point of discontinuity, and the series will have the expected value of e−1 . 4.13 Consider the representation as a Fourier series of the displacement of a string lying in the interval 0 ≤ x ≤ L and fixed at its ends, when it is pulled aside by y0 at the point x = L/4. Sketch the continuations for the region outside the interval that will (a) (b) (c) (d) (e)

produce a series of period L, produce a series that is antisymmetric about x = 0, and produce a series that will contain only cosine terms. What are (i) the periods of the series in (b) and (c) and (ii) the value of the “a0 -term” in (c)? Show that a typical term of the series obtained in (b) is nπx nπ 32y0 sin . sin 2 2 3n π 4 L

Parts (a), (b) and (c) of Figure 4.2 show the three required continuations. Condition (b) will result in a series containing only sine terms, whilst condition (c) requires the continued function to be symmetric about x = 0. (d) (i) The period in both cases, (b) and (c), is clearly 2L. (ii) The average value of the displacement is found from “the area under the triangular curve” to be ( 12 Ly0 )/L = 12 y0 , and this is the value of the “a0 -term”. (e) For the antisymmetric continuation there will be no cosine terms. The sine term coefficients (for a period of 2L) are given by 2 bn = 2 2L



L

f (x) sin(nkx) dx, where k = 2π/2L = π/L.

0

Here use has been made of the antisymmetry about x = 0 of both f (x) and the sine functions. However, because of the change in analytic form of f (x) between x < L/4 and

63

Fourier series

0

L

0

L

2L

0

L

2L

0

L

2L

(a)

(b)

(c)

Figure 4.2 Plucked string with fixed ends: (a)–(c) show possible mathematical continuations; (b) is antisymmetric about 0 and (c) is symmetric.

x > L/4, the integral will have to be split into two parts. Thus  L/4    L  4 2y0 4x 4x sin(nkx) dx + − sin(nkx) dx bn = L L 3L 0 L/4 3  L/4   L 8y0 3x sin(nkx) dx + (L − x) sin(nkx) dx = 3L2 0 L/4    L/4 3 cos(nkx) 8y0 3x cos(nkx) L/4 dx = − + 2 3L nk nk 0 0 !      L cos(nkx) L cos(nkx) L x cos(nkx) L dx . + − + − nk nk nk L/4 L/4 L/4 Evaluation of the remaining integrals then yields   8y0 3 sin(nkx) L/4 L cos(nπ) 3L cos(nπ/4) − −0+ bn = − 3L2 4n(π/L) n2 k 2 n(π/L) 0   ! sin(nkx) L L cos(nπ/4) L cos(nπ) L cos(nπ/4) + − − + n(π/L) n(π/L) 4n(π/L) n2 k 2 L/4 =

   nπ  32y0 8y0 3L2 sin(nπ/4) L2 sin(nπ) L2 sin(nπ/4) − + sin . = 3L2 n2 π 2 n2 π 2 n2 π 2 3n2 π 2 4

A typical term is therefore  nπx   nπ  32y0 sin . sin 3n2 π 2 4 L We note that every fourth term (n = 4m with m an integer) will be missing.

64

Fourier series 4.15 The Fourier series for the function y(x) = |x| in the range −π ≤ x < π is ∞ π 4  cos(2m + 1)x − . 2 π m=0 (2m + 1)2

y(x) =

By integrating this equation term by term from 0 to x, find the function g(x) whose Fourier series is ∞ 4  sin(2m + 1)x . π m=0 (2m + 1)3

Using these results, determine, as far as possible by inspection, the form of the functions of which the following are the Fourier series: (a) cos θ +

1 1 cos 3θ + cos 5θ + · · · ; 9 25

(b) sin θ + (c)

1 1 sin 3θ + sin 5θ + · · · ; 27 125

  πx L2 4L2 1 2πx 1 3πx − 2 cos − cos + cos − ··· . 3 π L 4 L 9 L

[You it helpful to first set x = 0 in the quoted result and so obtain values for So =  may find (2m + 1)−2 and other sums derivable from it.]

First, define S=

 all n=0

n−2 ,

So =



n−2 ,

Se =

odd n



n−2 .

even n=0

Clearly, Se = 14 S. Now set x = 0 in the quoted result to obtain 0=

∞ π π 4 4 1 = − So . − 2 2 π m=0 (2m + 1) 2 π

Thus, So = π 2 /8. Further, S = So + Se = So + 14 S; it follows that S = π 2 /6 and, by subtraction, that Se = π 2 /24. We now consider  x the integral  x of y(x) = |x| from 0 to x. 1 (i) For x < 0, |x| dx = (−x) dx = − x 2 . 2 0 0  x  x 1 |x| dx = x dx = x 2 . (ii) For x > 0, 2 0 0 Integrating the series term by term gives ∞ πx 4  sin(2m + 1)x − . 2 π m=0 (2m + 1)3

65

Fourier series

Equating these two results and isolating the series gives ∞ 4  sin(2m + 1)x = 12 x(π − x) for x ≥ 0, π m=0 (2m + 1)3

= 12 x(π + x) for x ≤ 0. Questions (a)–(c) are to be solved largely through inspection and so detailed working is not (cannot be) given. (a) Straightforward substitution of θ for x and rearrangement of the original Fourier series give g1 (θ) = 14 π( 12 π − |θ|). (b) Straightforward substitution of θ for x and rearrangement of the integrated Fourier series give g2 (θ) = 18 πθ(π − |θ|). (c) This contains only cosine terms and is therefore an even function of x. Its average value (given by the a0 term) is 13 L2 . Setting x = 0 gives   4L2 L2 1 1 − 2 1 − + − ··· f (0) = 3 π 4 9 L2 4L2 = − 2 (So − Se ) 3 π   4L2 π 2 π2 L2 − 2 − = 0. = 3 π 8 24 Setting x = L gives   1 1 L2 4L2 f (L) = − 2 −1 − − − · · · 3 π 4 9 2 2 4L L − 2 (−S) = L2 . = 3 π All of this evidence suggests that f (x) = x 2 (which it is). 4.17 Find the (real) Fourier series of period 2 for f (x) = cosh x and g(x) = x 2 in the range −1 ≤ x ≤ 1. By integrating the series for f (x) twice, prove that   ∞  (−1)n+1 1 1 5 = − . n2 π 2 (n2 π 2 + 1) 2 sinh 1 6 n=1

Since both functions are even, we need consider only constants and cosine terms. The series for x 2 can be calculated directly or, more easily, by using the result of the final part of Problem 4.15 with L set equal to 1: ∞ 4  (−1)n 1 cos πnx for −1 ≤ x ≤ 1. g(x) = x = + 2 3 π n=1 n2 2

66

Fourier series

For f (x) = cosh x,  1 2 a0 = 2 cosh x dx = 2 sinh(1), 2 0  1 2 cosh x cos(nπx) dx an = 2 2 0    1 sinh x sin(nπx) cosh x sin(nπx) 1 dx =2 −2 nπ nπ 0 0   sinh x cos(nπx) 1 an =0+2 − 2 2. 2 2 nπ nπ 0 Rearranging this gives an = Thus,

(−1)n 2 sinh(1) . 1 + n2 π 2

 ∞  (−1)n cos nπx . cosh x = sinh(1) 1 + 2 2π 2 1 + n n=1 

We now integrate this expansion twice from 0 to x (anticipating that we will recover a hyperbolic cosine function plus some additional terms). Since sinh(0) = sin(mπ0) = 0, the first integration yields   ∞  (−1)n sinh x = sinh(1) x + 2 sin nπx . nπ(1 + n2 π 2 ) n=1 For the second integration we use cosh(0) = cos(mπ0) = 1 to obtain   ∞  (−1)n+1 1 2 x +2 [cos(nπx) − 1] . cosh(x) − 1 = sinh(1) 2 n2 π 2 (1 + n2 π 2 ) n=1 However, this expansion must be the same as the original expansion for cosh(x) after a Fourier series has been substituted for the 12 sinh(1)x 2 term. The coefficients of cos nπx in the two expressions must be equal; in particular, the equality of the constant terms (formally cos nπx with n = 0) requires that sinh(1) − 1 =

∞  1 1 (−1)n+2 sinh(1) + 2 sinh(1) , 2 3 n2 π 2 (1 + n2 π 2 ) n=1

i.e. ∞  n=1

as stated in the question.

1 (−1)n+1 = 2 2 2 2 n π (n π + 1) 2



 1 5 − , sinh 1 6

67

Fourier series 4.19 Demonstrate explicitly for the odd (about x = 0) square-wave function that Parseval’s theorem is valid. You will need to use the relationship ∞ 

π2 1 = . (2m + 1)2 8 m=0 Show that a filter that transmits frequencies only up to 8π/T will still transmit more than 90% of the power in a square-wave voltage signal of period T .

As stated in the solution to Problem 4.7, and in virtually every textbook, the odd squarewave function has only the odd harmonics present in its Fourier sine series representation. The coefficient of the sin(2m + 1)πx term is b2m+1 =

4 . (2m + 1)π

For a periodic function of period L whose complex Fourier coefficients are cr , or whose cosine and sine coefficients are ar and br , respectively, Parseval’s theorem for one function states that  ∞  1 x0 +L 2 |f (x)| dx = |cr |2 L x0 r=−∞ =

1

a 2 0

2

+

1 2

∞  (ar2 + br2 ), r=1

and therefore requires in this particular case, in which all the ar are zero and L = 2, that  ∞ ∞ 16 1 1 2 1 1 = b = | ± 1|2 dx = 1. 2 m=0 (2m + 1)2 π 2 2 n=1 n 2 −1 Since ∞ 

π2 1 = , (2m + 1)2 8 m=0 this reduces to the identity 1 16 π 2 = 1. 2 π2 8 The power at any particular frequency in an electrical signal is proportional to the square of the amplitude at that frequency, i.e. to |bn |2 in the present case. If the filter passes only frequencies up to 8π/T = 4ω, then only the n = 1 and the n = 3 components will be passed. They contribute a fraction   π2 1 1 + ÷ = 0.901 1 9 8 of the total, i.e. more than 90%.

68

Fourier series 4.21 Find the complex Fourier series for the periodic function of period 2π defined in the range −π ≤ x ≤ π by y(x) = cosh x. By setting x = 0 prove that ∞   (−1)n 1 π = − 1 . n2 + 1 2 sinh π n=1

We first note that, although cosh x is an even function of x, e−inx is neither even nor odd. Consequently it will not be possible to convert the integral into one over the range 0 ≤ x ≤ π. The complex Fourier coefficients cn (−∞ < n < ∞) are therefore calculated as  π 1 cosh x e−inx dx 2π −π  π  1  −inx+x 1 e + e−inx−x dx = 2π −π 2  π  π 1 e(1−in)x 1 e(−1−in)x = + 4π 1 − in −π 4π −1 − in −π

cn =

1 (1 + in)(−1)n (2 sinh π) − (1 − in)(−1)n (−2 sinh π) 4π 1 + n2 (−1)n 4 sinh(π) = . 4π(1 + n2 ) =

Thus, cosh x =

∞  (−1)n sinh π inx e . π(1 + n2 ) n=−∞

We now set x = 0 on both sides of the equation: 1= ⇒

∞  (−1)n sinh π , π(1 + n2 ) n=−∞

∞  (−1)n π . = 2 1+n sinh π n=−∞

Separating out the n = 0 term, and noting that (−1)n = (−1)−n , now gives ∞  (−1)n π 1+2 = 2 1 + n sinh π n=1

and hence the stated result.

69

Fourier series 4.23 The complex Fourier series for the periodic function generated by f (t) = sin t for 0 ≤ t ≤ π/2, and repeated in every subsequent interval of π/2, is sin(t) =

∞ 2  4ni − 1 i4nt e . π n=−∞ 16n2 − 1

Apply Parseval’s theorem to this series and so derive a value for the sum of the series 65 145 16n2 + 1 17 + + + ··· + + ··· . 2 2 2 (15) (63) (143) (16n2 − 1)2

Applying Parseval’s theorem (see Solution 4.19) in a straightforward manner to the given equation: 2 π



π/2

sin2 (t) dt =

0

∞ 4  4ni − 1 −4ni − 1 , π 2 n=−∞ 16n2 − 1 16n2 − 1

∞ 4  16n2 + 1 2 1π = 2 , π 2 2 π n=−∞ (16n2 − 1)2 ∞  16n2 + 1 π2 =1+2 , 8 (16n2 − 1)2 n=1



∞  π2 − 8 16n2 + 1 = . (16n2 − 1)2 16 n=1

To obtain the second line we have used the standard result that the average value of the square of a sinusoid is 1/2. 4.25 Show that Parseval’s theorem for two real functions whose Fourier expansions have cosine and sine coefficients an , bn and αn , βn takes the form  ∞ 1 1 1 L f (x)g(x) dx = a0 α0 + (an αn + bn βn ). L 0 4 2 n=1 (a) Demonstrate that for g(x) = sin mx or cos mx this reduces to the definition of the Fourier coefficients. (b) Explicitly verify the above result for the case in which f (x) = x and g(x) is the square-wave function, both in the interval −1 ≤ x ≤ 1. [Note that g = g ∗ , and it is the integral of f g ∗ that will have to be formally evaluated using the complex Fourier series representations of the two functions.]

If cn and γn are the complex Fourier coefficients for the real functions f (x) and g(x) that have real Fourier coefficients an , bn and αn , βn , respectively, then cn = 12 (an − ibn ) c−n =

1 (a 2 n

+ ibn )

and

γn = αn − iβn ,

and

γ−n = αn + iβn .

70

Fourier series

The two functions can be written as



 2πinx , L n=−∞   ∞  2πinx γn exp . g(x) = L n=−∞

f (x) =

∞ 

cn exp

(∗)

Thus, f (x)g ∗ (x) =

∞ 

cn g ∗ (x) exp

n=−∞



 2πinx . L

Integrating this equation with respect to x over the interval (0, L) and dividing by L, we find     ∞  1 L 1 L ∗ 2πinx ∗ dx f (x)g (x) dx = cn g (x) exp L 0 L 0 L n=−∞   ∗   L ∞  −2πinx 1 cn g(x) exp dx = L 0 L n=−∞ =

∞ 

cn γn∗ .

n=−∞

To obtain the last line we have used the inverse of relationship (∗). Dividing up the sum over all n into a sum over positive n, a sum over negative n and the n = 0 term, and then substituting for cn and γn , gives  ∞ 1 1 L ∗ f (x)g (x) dx = (an − ibn )(αn + iβn ) L 0 4 n=1 ∞

+

1 1 (an + ibn )(αn − iβn ) + a0 α0 4 n=1 4 ∞

=

1 1 (2an αn + 2bn βn ) + a0 α0 4 n=1 4

=

1 1 (an αn + bn βn ) + a0 α0 , 2 n=1 4



i.e. the stated result. (a) For g(x) = sin mx, βm = 1 and all other αn and βn are zero. The above equation then reduces to  1 L 1 f (x) sin(mx) dx = bn , L 0 2 which is the normal definition of bn . Similarly, setting g(x) = cos mx leads to the normal definition of an .

71

Fourier series

(b) For the function f (x) = x in the interval −1 < x ≤ 1, the sine coefficients are  2 1 bn = x sin nπx dx 2 −1  1 =2 x sin nπx dx 0 !    1 cos nπx −x cos nπx 1 dx + =2 nπ nπ 0 0   (−1)n+1 " sin nπx #1 + =2 nπ n2 π 2 0 2(−1)n+1 . = nπ As stated in Problem 4.19, for the (antisymmetric) square-wave function βn = 4/(nπ) for odd n and βn = 0 for even n. Now the integral  0    1 1 L 1 1 ∗ f (x)g (x) dx = (−1)x dx + (+1)x dx = , L 0 2 −1 2 0 whilst ∞ 1  4 2(−1)n+1 4 π2 1 4  1 1 bn βn = = 2 = 2 = . 2 2 n=1 2 n odd nπ nπ π n odd n π 8 2  The value of the sum n−2 for odd n is taken from So in the solution to Problem 4.15. Thus, the two sides of the equation agree, verifying the validity of Parseval’s theorem in this case.

5

Integral transforms

5.1 Find the Fourier transform of the function f (t) = exp(−|t|). (a) By applying Fourier’s inversion theorem prove that  ∞ π cos ωt dω. exp(−|t|) = 2 1 + ω2 0 (b) By making the substitution ω = tan θ , demonstrate the validity of Parseval’s theorem for this function.

As the function |t| is not representable by the same integrable function throughout the integration range, we must divide the range into two sections and use different explicit expressions for the integrand in each:  ∞ 1 ˜ e−|t| e−iωt dt f (ω) = √ 2π −∞  ∞  0 1 1 = √ e−(1+iω)t dt + √ e(1−iω)t dt 2π 0 2π −∞   1 1 1 + = √ 2π 1 + iω 1 − iω 1 2 = √ . 2π 1 + ω2 (a) Substituting this result into the inversion theorem gives  ∞ 1 2 eiωt dω. exp−|t| = √ √ 2π −∞ 2π (1 + ω2 ) Equating the real parts on the two sides of this equation and noting that the resulting integrand is symmetric in ω, shows that  2 ∞ cos ωt dω, exp−|t| = π 0 (1 + ω2 ) as given in the question. (b) For Parseval’s theorem, which states that  ∞  ∞ |f (t)|2 dt = |f˜(ω)|2 dω, −∞

72

−∞

73

Integral transforms

we first evaluate





−∞

 |f (t)|2 dt = =2

0

 e2t dt +

−∞  ∞

e

e−2t =2 −2 The second integral, over ω, is   ∞ |f˜(ω)|2 dω = 2 −∞

4 π 4 = π =

e−2t dt

0

0





−2t

dt

∞ = 1. 0



2 dω, set ω equal to tan θ, π(1 + ω2 )2 0  π/2 1 sec2 θ dθ sec4 θ 0  π/2 4 1π cos2 θ dθ = = 1, π 2 2 0

i.e. the same as the first one, thus verifying the theorem for this function. 5.3 Find the Fourier transform of H (x − a)e−bx , where H (x) is the Heaviside function.

The Heaviside function H (x) has value 0 for x < 0 and value 1 for x ≥ 0. Write H (x − a)e−bx = h(x) with b assumed > 0. Then,  ∞ 1 ˜ H (x − a)e−bx e−ikx dx h(k) = √ 2π −∞  ∞ 1 e−bx−ikx dx = √ 2π a  −bx−ikx ∞ e 1 = √ 2π −b − ik a e−ba b − ik 1 e−ba e−ika = e−ika √ = √ . 2π b + ik 2π b2 + k 2 This same result could be obtained by setting y = x − a, finding the transform of e−ba e−by , and then using the translation property of Fourier transforms. 5.5 By taking the Fourier transform of the equation d 2φ − K 2 φ = f (x), dx 2 show that its solution, φ(x), can be written as  ∞ ikx $ −1 e f (k) φ(x) = √ dk, k 2π −∞ 2 + K 2 where f$(k) is the Fourier transform of f (x).

74

Integral transforms

We take the Fourier transform of each term of d 2φ − K 2 φ = f (x) dx 2 to give 1 √ 2π





−∞

d 2 φ −ikx 1 ˜ e dx − K 2 φ(k) =√ 2 dx 2π





f (x) e−ikx dx.

−∞

Since φ must vanish at ±∞, the first term can be integrated twice by parts with no contributions at the end-points. This gives the full equation as ˜ − K 2 φ(k) ˜ = f˜(k). −k 2 φ(k) Now, by the Fourier inversion theorem,  ∞ 1 ˜ eikx dk φ(x) = √ φ(k) 2π −∞  ∞ ˜ f (k) eikx 1 dk. = −√ 2π −∞ k 2 + K 2 Note The principal advantage of this Fourier approach to a set of one or more linear differential equations is that the differential operators act only on exponential functions whose exponents are linear in x. This means that the derivatives are no more than multiples of the original function and what were originally differential equations are turned into algebraic ones. As the differential equations are linear the algebraic equations can be solved explicitly for the transforms of their solutions, and the solutions themselves may then be found using the inversion theorem. The “price” to be paid for this great simplification is that the inversion integral may not be tractable analytically, but, as a last resort, numerical integration can always be employed. 5.7 Find the Fourier transform of the unit rectangular distribution  1 |t| < 1, f (t) = 0 otherwise. Determine the convolution of f with itself and, without further integration, determine its transform. Deduce that  ∞  ∞ 2π sin2 ω sin4 ω . dω = π, dω = 2 4 ω ω 3 −∞ −∞

The function to be transformed is unity in the range −1 ≤ t ≤ 1 and so 1 f˜(ω) = √ 2π



1

1 1 e−iωt dt = √ 2π −1



e−iω − eiω −iω



2 sin ω =√ . 2π ω

75

Integral transforms

Denote by p(t) the convolution of f with itself and, in the second line of the calculation below, change the integration variable from s to u = t − s:  ∞  1 p(t) ≡ f (t − s)f (s) ds = f (t − s) 1 ds −∞ t−1

=

−1 t+1





f (u)(−du) =

t+1

f (u)du. t−1

It follows that p(t) =

(t + 1) − (−1) 0 > t > −2 1 − (t − 1)

2 − |t|

=

2>t >0

0

0 < |t| < 2, otherwise.

The transform of p is given directly by the convolution theorem √ [which states that if h(t), ˜ as given by h = f ∗ g, is the convolution of f and g, then h˜ = 2π f˜ g] ˜ p(ω) =



4 sin2 ω 2 sin ω 2 sin ω =√ 2π √ . √ 2π ω 2π ω 2π ω2

Noting that the two integrals to be evaluated have as integrands the squares of functions that are essentially the known transforms of simple functions, we are led to apply Parseval’s theorem to each. Applying the theorem to f (t) and p(t) yields  ∞  ∞  ∞ 4 sin2 ω sin2 ω 2 dω = |f (t)| dt = 2 ⇒ = π, 2 2 −∞ 2πω −∞ −∞ ω 



and −∞

16 sin4 ω dω = 2π ω4

 ⇒

∞ −∞



0

 (2 + t) dt + 2

−2



(2 + t)3 = 3 8 8 = + , 3 3 sin4 ω 2π . dω = ω4 3

0



2

(2 − t)2 dt

0

(2 − t)3 − 3 −2

2 0

5.9 By finding the complex Fourier series for its LHS show that either side of the equation ∞  n=−∞

δ(t + nT ) =

∞ 1  −2π nit/T e T n=−∞

can represent a periodic train of impulses. By expressing the function f (t + nX), in which X is a constant, in terms of the Fourier transform f˜(ω) of f (t), show that √   ∞ ∞  2π  ˜ 2nπ f f (t + nX) = e2π nit/X . X X n=−∞ n=−∞ This result is known as the Poisson summation formula.

76

Integral transforms

Denote by g(t) the periodic function Fourier coefficients are given by 1 cn = T



T

g(t) e 0

∞

−inωt

n=−∞

1 dt = T

δ(t + nT ) with 2π/T = ω. Its complex 

T

δ(t) e−inωt dt =

0

1 . T

Thus, by the inversion theorem, its Fourier series representation is g(t) =

∞ ∞ ∞    1 inωt 1 −inωt 1 −i2nπt/T e e e = = , T T T n=−∞ n=−∞ n=−∞

showing that both this sum and the original one are representations of a periodic train of impulses. In this result, ∞  n=−∞

δ(t + nT ) =

∞ 1  −2πnit/T e , T n=−∞

we now make the changes of variable t → ω, n → −n and T → 2π/X and obtain   ∞ X  inXω 2πn = δ ω− e . X 2π n=−∞ n=−∞ ∞ 

(∗)

If we denote f (t + nX) by fnX (t) then, by the translation theorem, we have f˜nX (ω) = einXω f˜(ω) and  ∞ 1 f˜nX (ω) eiωt dω f (t + nX) = √ 2π −∞  ∞ 1 einXω f˜(ω) eiωt dω, =√ 2π −∞  ∞ ∞ ∞   1 f (t + nX) = √ einXω dω, use (∗) above, f˜(ω) eiωt 2π −∞ n=−∞ n=−∞    ∞ ∞ 2πn 1 2π  δ ω− =√ f˜(ω) eiωt dω X n=−∞ X 2π −∞ √   ∞ 2π  ˜ 2πn ei2πnt/X . f = X n=−∞ X In the final line we have made use of the properties of a δ-function when it appears as a factor in an integrand.

77

Integral transforms 5.11 For a function f (t) that is non-zero only in the range |t| < T /2, the full frequency spectrum f˜(ω) can be constructed, in principle exactly, from values at discrete sample points ω = n(2π/T ). Prove this as follows. (a) Show that the coefficients of a complex Fourier series representation of f (t) with period T can be written as √   2π ˜ 2πn f . cn = T T (b) Use this result to represent f (t) as an infinite sum in the defining integral for f˜(ω), and hence show that     ∞  ωT 2πn sinc nπ − , f˜ f˜(ω) = T 2 n=−∞ where sinc x is defined as (sin x)/x.

(a) The complex coefficients for the Fourier series for f (t) are given by cn =

1 T



T /2

f (t) e−i2πnt/T dt.

−T /2

But, we also know that the Fourier transform of f (t) is given by 1 f˜(ω) = √ 2π





f (t) e −∞

−iωt

1 dt = √ 2π



T /2

f (t) e−iωt dt.

−T /2

√   Comparison of these two equations shows that cn = T1 2π f˜ 2πn . T (b) Using the Fourier series representation of f (t), the frequency spectrum at a general frequency ω can now be constructed as 1 f˜(ω) = √ 2π



T /2

f (t) e−iωt dt     T /2   ∞ 2πn 1√ 1 i2πnt/T 2π f˜ e = √ e−iωt dt T 2π −T /2 n=−∞ T   2πn ωT       − 2 sin ∞ ∞  1  ˜ 2πn 2πn ωT 2 2 ˜ = = f f sinc nπ − . 2πn T n=−∞ T T 2 n=−∞ −ω T −T /2

This final formula gives a prescription for calculating the frequency spectrum f˜(ω) of f (t) for any ω, given the spectrum at the (admittedly infinite number of) discrete values ω = 2πn/T . The sinc functions give the weights to be assigned to the known discrete values; of course, the weights vary as ω is varied, with, as expected, the largest weights for the nth contribution occurring when ω is close to 2πn/T .

78

Integral transforms 5.13 Find the Fourier transform specified in part (a) and then use it to answer part (b). (a) Find the Fourier transform of

 f (γ , p, t) =

e−γ t sin pt 0

t > 0, t < 0,

where γ (> 0) and p are constant parameters. (b) The current I (t) flowing through a certain system is related to the applied voltage V (t) by the equation  ∞ K(t − u)V (u) du, I (t) = −∞

where K(τ ) = a1 f (γ1 , p1 , τ ) + a2 f (γ2 , p2 , τ ). The function f (γ , p, t) is as given in part (a) and all the ai , γi (> 0) and pi are fixed parameters. By considering the Fourier transform of I (t), find the relationship that must hold between a1 and a2 if the total net charge Q passed through the system (over a very long time) is to be zero for an arbitrary applied voltage.

(a) Write the given sine function in terms of exponential functions. Its Fourier transform is then easily calculated as  ∞ (−γ −iω+ip)t 1 e − e(−γ −iω−ip)t f˜(ω, γ , p) = √ dt 2i 2π 0   1 1 −1 1 = √ + 2π 2i −γ − iω + ip −γ − iω − ip p 1 . = √ 2π (γ + iω)2 + p 2 (b) Since the current is given by the convolution  I (t) =

∞ −∞

K(t − u)V (u) du,

the convolution theorem implies that the Fourier transforms of I , K and V are related by √ ˜ V˜ (ω) with, from part (a), I˜(ω) = 2π K(ω) 1 ˜ K(ω) =√ 2π



 a1 p 1 a2 p2 . + (γ1 + iω)2 + p12 (γ2 + iω)2 + p22

Now, by expressing I (t ) in its Fourier integral form, we can write  Q(∞) =

∞ −∞

I (t ) dt =



∞ −∞

dt





−∞

1 √ I˜(ω) eiωt dω. 2π

79

Integral transforms

But

∞

−∞



eiωt dt = 2πδ(ω) and so  ∞ 1 Q(∞) = √ I˜(ω) 2πδ(ω) dω 2π −∞ √ √ 2π ˜ ˜ = √ I (0) = 2π 2π K(0) V˜ (0) 2π   a2 p 2 a1 p1 1 + 2 V˜ (0). = 2π √ γ2 + p22 2π γ12 + p12

For Q(∞) to be zero for an arbitrary V (t), we must have a2 p 2 a1 p1 + 2 = 0, 2 2 γ1 + p1 γ2 + p22 and so this is the required relationship. 5.15 A linear amplifier produces an output that is the convolution of its input and its response function. The Fourier transform of the response function for a particular amplifier is ˜ K(ω) = √

iω 2π(α + iω)2

.

Determine the time variation of its output g(t) when its input is the Heaviside step function.

This result is immediate, since differentiating the definition of a Fourier transform (under the integral sign) gives  ∞   ∞ d f˜(ω) i ∂ −i 2 −iωt i =√ f (t) e dt = √ tf (t) e−iωt dt, dω 2π ∂ω 2π −∞ −∞ i.e. the transform of tf (t). Since the amplifier’s output is the convolution of its input and response function, we will need the Fourier transforms of both to determine that of its output (using the convolution theorem). We already have that of its response function. The input Heaviside step function H (t) has a Fourier transform  ∞  ∞ 1 1 1 1 . H (t) e−iωt dt = √ e−iωt dt = √ H˜ (ω) = √ 2π −∞ 2π 0 2π iω Thus, using the convolution theorem, √ 1 1 iω ˜ g(ω) = 2π √ √ 2π (α + iω)2 2π iω 1 1 = √ (α + iω)2 2π   i 1 ∂ =√ 2π ∂ω α + iω & ∂ %  −αt F e H (t) =i ∂ω  = F te−αt H (t) ,

80

Integral transforms

where we have used the “library” result to recognize the transform of a decaying exponential in the penultimate line and the result proved above in the final step. The output of the amplifier is therefore of the form g(t) = te−αt for t > 0 when its input takes the form of the Heaviside step function. 5.17 [This problem can only be attempted if Problem 5.16 of the main text has been studied.] For some ion–atom scattering processes, the spherically symmetric potential V (r) of the previous problem may be approximated by V = |r1 − r2 |−1 exp(−μ|r1 − r2 |). Show, using the result of the worked example in Subsection 5.1.9, that the probability that the ion will scatter from, say, p1 to p 1 is proportional to (μ2 + k 2 )−2 , where k = |k| and k is as given in part (c) of the previous problem.

As shown in Problem 5.16, the Fourier transform of a spherically symmetric potential V (r) is given by $(k) = V

1 (2π)3/2 k





4πV (r)r sin kr dr. 0

The ion–atom interaction potential in this particular example is V (r) = r −1 exp(−μr). As this is spherically symmetric, we may apply the result to it. Substituting for V (r) gives  1 ∞ e−μr $ r sin kr dr M ∝ V (k) ∝ k 0 r  ∞ 1 e−μr+ikr dr = Im k 0   1 −1 = Im k −μ + ik k 1 . = k μ2 + k 2 Since the probability of the ion scattering from p1 to p 1 is proportional to the modulus squared of M, the probability is ∝ |M|2 ∝ (μ2 + k 2 )−2 . 5.19 Find the Laplace transforms of t −1/2 and t 1/2 , by setting x 2 = ts in the result  ∞ √ exp(−x 2 ) dx = 12 π. 0

√ Setting x 2 = st, and hence 2x dx = s dt and dx = s dt/(2 st), we obtain √ √ s −1/2 π t , e dt = 2 2 0 '  ∞  −1/2 π −1/2 −st . ≡ L t t e dt = s 0 





−st

81

Integral transforms

Integrating the LHS of this result by parts yields 

e

−st



∞ 2t 1/2 0

'





(−s) e

−st

2t

1/2

dt =

0

π . s

The first term vanishes at both limits, whilst the second is a multiple of the required Laplace transform of t 1/2 . Hence, 

L t

1/2









e

−st 1/2

t

0

1 dt = 2s

'

π . s

5.21 Use the properties of Laplace transforms to prove the following without evaluating any Laplace integrals explicitly:  √ −7/2 πs ; (a) L t 5/2 = 15 8 (b) L [ (sinh at)/t ] =

1 2

ln [(s + a)/(s − a)] ,

s > |a|;

(c) L [ sinh at cos bt ] = a(s − a + b )[(s − a) + b2 ]−1 [(s + a)2 + b2 ]−1 . 2

2

2

2

(a) We use the general result for Laplace transforms that  d n f¯ (s) L t n f (t) = (−1)n , ds n

for n = 1, 2, 3, . . . .

If we take n = 2, then f (t) becomes t 1/2 , for which we found the Laplace transform in Problem 5.19:  √ −3/2    d2 πs L t 5/2 = L t 2 t 1/2 = (−1)2 2 ds 2 √ √    3 5 −7/2 15 π −7/2 π − − s s = . = 2 2 2 8 (b) Here we apply a second general result for Laplace transforms which states that 

L

f (t) t



 =



f¯ (u) du,

s

provided limt→0 [f (t)/t] exists, which it does in this case. 

sinh(at) L t







a du, u > |a|, − a2 s    1 1 ∞ 1 − du = 2 s u−a u+a   1 s+a = ln , s > |a|. 2 s−a =

u2

82

Integral transforms

(c) The translation property of Laplace transforms can be used here to deal with the sinh(at) factor, as it can be expressed in terms of exponential functions:   L [ sinh(at) cos(bt) ] = L 12 eat cos(bt) − L 12 e−at cos(bt) s−a s+a 1 1 = − 2 2 2 (s − a) + b 2 (s + a)2 + b2 (s 2 − a 2 )2a + 2ab2 1 = 2 [(s − a)2 + b2 ][(s + a)2 + b2 ] a(s 2 − a 2 + b2 ) = . [(s − a)2 + b2 ][(s + a)2 + b2 ] The result is valid for s > |a|. 5.23 This problem is concerned with the limiting behavior of Laplace transforms. (a) If f (t) = A + g(t), where A is a constant and the indefinite integral of g(t) is bounded as its upper limit tends to ∞, show that lim s f¯(s) = A.

s→0

(b) For t > 0, the function y(t) obeys the differential equation dy d 2y +a + by = c cos2 ωt, dt 2 dt ¯ ¯ → c/2b as s → 0. where a, b and c are positive constants. Find y(s) and show that s y(s) Interpret the result in the t-domain.

(a) From the definition, 



[A + g(t)] e−st dt  −st ∞  T Ae = + lim g(t) e−st dt, T →∞ 0 −s 0  T ¯ s f (s) = A + s lim g(t) e−st dt. f¯(s) =

0

T →∞ 0

Now, for s ≥ 0,

    lim T →∞

T

g(t) e

0

−st

       dt  ≤  lim T →∞

T

0

  g(t) dt  < B, say.

Thus, taking the limit s → 0, lim s f¯(s) = A ± lim sB = A.

s→0

s→0

(b) We will need   L cos2 ωt = L 12 cos 2ω + 12 =

2(s 2

1 s + . 2 + 4ω ) 2s

83

Integral transforms

Taking the transform of the differential equation yields

 1 s ¯ + by¯ = c −y (0) − sy(0) + s y¯ + a[−y(0) + s y] + . 2(s 2 + 4ω2 ) 2s



2

This can be rearranged as   s2 1 c + + sy (0) + asy(0) + s 2 y(0) 2(s 2 + 4ω2 ) 2 s y¯ = . s 2 + as + b In the limit s → 0, this tends to (c/2)/b = c/(2b), a value independent of that of a and the initial values of y and y . The s = 0 component of the transform corresponds to long-term values, when a steady state has been reached and rates of change are negligible. With the first two terms of the differential equation ignored, it reduces to by = c cos2 ωt, and, as the average value of cos2 ωt is 12 , the solution is the more or less steady value of y = 12 c/b. 5.25 The function fa (x) is defined as unity for 0 < x < a and zero otherwise. Find its Laplace transform f¯ a (s) and deduce that the transform of xfa (x) is 1  1 − (1 + as)e−sa . s2 Write fa (x) in terms of Heaviside functions and hence obtain an explicit expression for  x ga (x) = fa (y)fa (x − y) dy. 0

Use the expression to write g¯ a (s) in terms of the functions f¯ a (s) and f¯ 2a (s), and their derivatives, and hence show that g¯ a (s) is equal to the square of f¯ a (s), in accordance with the convolution theorem.

From their definitions,



a

1 (1 − e−sa ), s 0  a 1 d f¯a a −sx = 2 (1 − e−sa ) − e−sa x fa (x) e dx = − ds s s 0  1 = 2 1 − (1 + as)e−sa . (∗) s f¯a (s) =

1 e−sx dx =

In terms of Heaviside functions, f (x) = H (x) − H (x − a), x and so the expression for ga (x) = 0 fa (y)fa (x − y) dy is  ∞ [H (y) − H (y − a)] [H (x − y) − H (x − y − a)] dy. −∞

This can be expanded as the sum of four integrals, each of which contains the common factors H (y) and H (x − y), implying that, in all cases, unless x is positive and greater than y, the integral has zero value. The other factors in the four integrands are generated

84

Integral transforms

analogously to the terms of the expansion (a − b)(c − d) = ac − ad − bc + bd:  ∞ H (y)H (x − y) dy −∞  ∞ H (y)H (x − y − a) dy − −∞  ∞ H (y − a)H (x − y) dy − −∞  ∞ H (y − a)H (x − y − a) dy. + −∞

In all four integrals the integrand is either 0 or 1 and the value of each integral is equal to the length of the y-interval in which the integrand is non-zero. r The first integral requires 0 < y < x and therefore has value x for x > 0. r The second integral requires 0 < y < x − a and therefore has value x − a for x > a and 0 for x < a. r The third integral requires a < y < x and therefore has value x − a for x > a and 0 for x < a. r The final integral requires a < y < x − a and therefore has value x − 2a for x > 2a and 0 for x < 2a. Collecting these together: x τ.

The boundary condition x(0) = 0 implies that A = 0, and ˙ x(0) =0



B(−e−t sin κt + κe−t cos κt) = 0



B = 0.

Thus G(t, τ ) = 0 for t < τ . The continuity of G at t = τ gives Ce−τ cos κτ + De−τ sin κτ = 0



D=−

C cos κτ . sin κτ

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Higher-order ordinary differential equations

The unit discontinuity in the derivative of G at t = τ requires (using s = sin κτ and c = cos κτ as shorthand) Ce−τ (−c − κs) + De−τ (−s + κc) − 0 = 1, # " c C −c − κs − (−s + κc) = eτ , s 2 C(−sc − κs + cs − κc2 ) = seτ , giving C=−

eτ sin κτ κ

and D =

eτ cos κτ . κ

Thus, for t > τ , eτ (− sin κτ cos κt + cos κτ sin κt)e−t κ e−(t−τ ) sin κ(t − τ ). = κ

G(t, τ ) =

This form verifies that the Green’s function is a function only of the difference t − τ and not of t and τ separately. The explicit solution to the given equation when f (t) = H (t) is thus 



x(t) =

G(t, τ )f (τ ) dτ 0

 =

t

G(t, τ )H (τ ) dτ , since G(t, τ ) = 0 for τ > t,  1 t −(t−τ ) e sin κ(t − τ ) dτ κ 0  t e−t eτ +iκ(t−τ ) dτ Im κ 0  iκt τ −iκτ τ =t e e e−t Im κ 1 − iκ τ =0  t  −t e − eiκt e Im . κ 1 − iκ 0

= = = =

Now multiplying both numerator and denominator by 1 + iκ to make the latter real gives e−t Im [ (et − eiκt )(1 + iκ) ] κ(1 + κ 2 ) e−t [ κ(et − cos κt) − sin κt ] = κ(1 + κ 2 )   1 −t 1 −t 1 − e cos κt − e sin κt . = 1 + κ2 κ

x(t) =

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Higher-order ordinary differential equations

The Laplace transform of this solution is given by   1 1 s+1 κ 1 − x¯ = − 1 + κ2 s (s + 1)2 + κ 2 κ (s + 1)2 + κ 2 =

(s + 1)2 + κ 2 − s(s + 1) − s (1 + κ 2 )s[ (s + 1)2 + κ 2 ]

=

1 . s[ (s + 1)2 + κ 2 ]

The Laplace transform of the original equation with the given initial conditions reads [ s 2 x¯ − 0s − 0 ] + 2[ s x¯ − 0 ] + (1 + κ 2 )x¯ =

1 , s

again showing that x¯ =

s[ s 2

1 1 = , 2 + 2s + 1 + κ ] s[ (s + 1)2 + κ 2 ]

and so confirming the solution reached using the Green’s function approach. 6.31 Find the Green’s function x = G(t, t0 ) that solves dx d 2x +α = δ(t − t0 ) 2 dt dt under the initial conditions x = dx/dt = 0 at t = 0. Hence solve d 2x dx = f (t), +α 2 dt dt where f (t) = 0 for t < 0. Evaluate your answer explicitly for f (t) = Ae−βt (t > 0).

It is clear that one solution, x(t), to the homogeneous equation has x¨ = −α x˙ and is therefore x(t) = Ae−αt . The equation is of second order and therefore has a second solution; this is the trivial (but perfectly valid) x is a constant. The CF is thus x(t) = Ae−αt + B. Let G(t, t0 ) =

Ae−αt + B,

0 ≤ t ≤ t0 ,

Ce−αt + D,

t > t0 .

Now, the initial conditions give x(0) = 0



A + B = 0,

˙ x(0) =0



−αA = 0

Thus G(t, t0 ) = 0 for 0 ≤ t ≤ t0 .



A = B = 0.

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Higher-order ordinary differential equations

The continuity/discontinuity conditions determine C and D through Ce−αt0 + D − 0 = 0, −αCe−αt0 − 0 = 1, G(t, t0 ) =

It follows that



C=−

eαt0 1 and D = . α α

1 [ 1 − e−α(t−t0 ) ] for t > t0 . α

The general formalism now gives the solution of dx d 2x = f (t) +α 2 dt dt as

 x(t) =

t

0

With f (t) = Ae

−βt

1 [ 1 − e−α(t−τ ) ]f (τ ) dτ. α

this becomes  t 1 [ 1 − e−α(t−τ ) ]Ae−βτ dτ x(t) = α 0  A t −βτ (e − e−αt e(α−β)τ ) dτ = α 0   1 − e−βt e−βt − e−αt =A − αβ α(α − β)   −βt α − β − αe + βe−αt =A βα(α − β)   α(1 − e−βt ) − β(1 − e−αt ) . =A βα(α − β)

This is the required explicit solution. 6.33 Solve

  2  dy d 2 y dy d 3y +2 = sin x. 2y 3 + 2 y + 3 dx dx dx 2 dx

The only realistic hope for this non-linear equation is to try to arrange it as an exact equation! We note that the second and fourth terms can be written as the derivative of a product, and that adding and subtracting 2y y will enable the first term to be written in a similar way. We therefore rewrite the equation as     d 2y dy dy d 2 y d d 2y 2 + 2y + (6 − 2) = sin x, dx dx dx dx dx dx 2       2  d 2y dy d dy d d 2y 2 + 2y + 2 = sin x. dx dx dx dx dx dx

102

Higher-order ordinary differential equations

This second form is obtained by noting that the final term on the LHS of the first equation happens to be an exact differential. Thus the whole of the LHS is an exact differential and one stage of integration can be carried out:  2 d 2y dy dy 2y 2 + 2y = − cos x + A. +2 dx dx dx We now note that the first and third terms of this integrated equation can be combined as the derivative of a product, whilst the second term is the derivative of y 2 . This allows a further step of integration:   d dy dy 2y + 2y dx dx dx   dy d(y 2 ) d 2y + dx dx dx dy ⇒ 2y + y2 dx d(y 2 ) + y2 dx

= − cos x + A, = − cos x + A, = − sin x + Ax + B, = − sin x + Ax + B.

At this stage an integrating factor is needed. However, as the LHS consists of the sum of the differentiated and undifferentiated forms of the same function, the required IF is simply ex . After multiplying through by this, we obtain d  x 2 e y = −ex sin x + Axex + Bex , dx   ⇒

y =e 2

−x

C+

x



(B + Au− sin u)e du u

= Ce−x + B + A(x − 1) − 12 (sin x− cos x). The last term in this final solution is obtained by considering 

x

 e sin u du = Im u

x

e(1+i)u du  (1+i)u x e = Im 1+i 1 = Im 2 (1 − i)e(1+i)x = 12 ex (sin x− cos x).

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Higher-order ordinary differential equations

6.35 Confirm that the equation 2x 2 y

d 2y + y2 = x2 dx 2



dy dx

2 (∗)

is homogeneous in both x and y separately. Make two successive transformations that exploit this fact, starting with a substitution for x, to obtain an equation of the form  2 dv dv d 2v −2 2 2 + + 1 = 0. dt dt dt By writing dv/dt = p, solve this equation for v = v(t) and hence find the solution to (∗).

The “net-power” (weight) of x in each of the terms is 2 − 2 = 0, 0, 2 − 2 = 0, i.e. they are all equal (to zero) and the equation is homogeneous in x. Similarly for y, the weights are 2, 2 and 2; and so the equation is also (separately) homogeneous in y. d d = e−t . The equation then reads Using the homogeneity in x, set x = et with dx dt     dy dy 2 , e−t + y 2 = e2t e−t dt dt    2 2 dy t −t d y −t dy 2 2t −2t 2ye e +y =e e −e , 2 dt dt dt  2 dy dy d 2y 2 +y = . 2y 2 − 2y dt dt dt 2e2t ye−t

d dt

Now using the homogeneity in y, set y = ev with dy dv dv dy = = ev dt dv dt dt

and

d 2y d = dt 2 dt

 ev

dv dt

 = ev

dv dv d 2v + ev 2 dt dt dt

and obtain  2ev ev



dv dt

2

  2 2 d v v v v dv 2v 2v dv +e =e − 2e e +e . dt 2 dt dt

Canceling e2v all through, this reduces to d 2v 2 2 + dt



dv dt

2 −2

dv + 1 = 0. dt

Since v does not appear in this equation undifferentiated, write dv/dt = p, obtaining 2

dp + p 2 − 2p + 1 = 0 dt



dp = − 12 (p − 1)2 . dt

104

Higher-order ordinary differential equations

This is separable: dp = − 12 dt (p − 1)2



(p − 1)−1 = + 12 t + A.

Rewriting p as dv/dt, we now have 1 dv −1= 1 dt t +A 2



  v − t = 2 ln A + 12 t + B.

Resubstituting for v and t now gives ln y = 2 ln(A + 12 ln x) + B + ln x, ⇒

y = x(C + D ln x)2 ,

where C = AeB/2 and D = 12 eB/2 .

7

Series solutions of ordinary differential equations

7.1 Find two power series solutions about z = 0 of the differential equation (1 − z2 )y − 3zy + λy = 0. Deduce that the value of λ for which the corresponding power series becomes an N th-degree polynomial UN (z) is N (N + 2). Construct U2 (z) and U3 (z).

If the equation is imagined divided through by (1 − z2 ) it is straightforward to see that, although z = ±1 are singular points of the equation, the point z = 0 is an ordinary point. We therefore expect two (uncomplicated!) series solutions with indicial values σ = 0 and σ = 1.  n (a) σ = 0 and y(z) = ∞ n=0 an z with a0 = 0. Substituting and equating the coefficients of zm , (1 − z2 )

∞ 

n(n − 1)an zn−2 − 3

n=0

∞ 

nan zn + λ

n=0

∞ 

an zn = 0,

n=0

(m + 2)(m + 1)am+2 − m(m − 1)am − 3mam + λam = 0, gives as the recurrence relation am+2 =

m(m − 1) + 3m − λ m(m + 2) − λ am = am . (m + 2)(m + 1) (m + 1)(m + 2)

Since this recurrence relation connects alternate coefficients am , and a0 = 0, only the coefficients with even indices are generated. All such coefficients with index higher than m will become zero, and the series will become an Nth-degree polynomial UN (z), if λ = m(m + 2) = N(N + 2) for some (even) m appearing in the series; here, this means any positive even integer N. To construct U2 (z) we need to take λ = 2(2 + 2) = 8. The recurrence relation gives a2 as 0−8 a2 = a0 = −4a0 ⇒ U2 (z) = a0 (1 − 4z2 ). (0 + 1)(0 + 2)  n (b) σ = 1 and y(z) = z ∞ n=0 an z with a0 = 0. Substituting and equating the coefficients of zm+1 , (1 − z ) 2

∞  n=0

(n + 1)nan z

n−1

−3

∞  n=0

(n + 1)an z

n+1



∞ 

an zn+1 = 0,

n=0

(m + 3)(m + 2)am+2 − (m + 1)mam − 3(m + 1)am + λam = 0, 105

106

Series solutions of ordinary differential equations

gives as the recurrence relation am+2 =

m(m + 1) + 3(m + 1) − λ (m + 1)(m + 3) − λ am = am . (m + 2)(m + 3) (m + 2)(m + 3)

Again, all coefficients with index higher than m will become zero, and the series will become an Nth-degree polynomial UN (z), if λ = (m + 1)(m + 3) = N(N + 2) for some (even) m appearing in the series; here, this means any positive odd integer N. To construct U3 (z) we need to take λ = 3(3 + 2) = 15. The recurrence relation gives a2 as a2 =

3 − 15 a0 = −2a0 . (0 + 2)(0 + 3)

Thus, U3 (z) = a0 (z − 2z3 ).

7.3 Find power series solutions in z of the differential equation zy − 2y + 9z5 y = 0. Identify closed forms for the two series, calculate their Wronskian, and verify that they are linearly independent. Compare the Wronskian with that calculated from the differential equation.

Putting the equation in its standard form shows that z = 0 is a singular point of the equation but, as −2z/z and 9z7 /z are finite as z → 0, it is a regular singular point. We therefore substitute a Frobenius-type solution, y(z) = z

σ

∞ 

an zn with a0 = 0,

n=0

and obtain ∞  (n + σ )(n + σ − 1)an zn+σ −1 n=0 ∞ ∞   n+σ −1 −2 (n + σ )an z +9 an zn+σ +5 = 0. n=0

n=0

Equating the coefficient of zσ −1 to zero gives the indicial equation as σ (σ − 1)a0 − 2σ a0 = 0



σ = 0, 3.

These differ by an integer and may or may not yield two independent solutions. The larger root, σ = 3, will give a solution; the smaller one, σ = 0, may not. (a) σ = 3. Equating the general coefficient of zm+2 to zero (with σ = 3) gives (m + 3)(m + 2)am − 2(m + 3)am + 9am−6 = 0.

107

Series solutions of ordinary differential equations

Hence the recurrence relation is 9am−6 , m(m + 3) a6p−6 9 (−1)p a0 =− a6p−6 = − = . 6p (6p + 3) 2p (2p + 1) (2p + 1)!

am = − ⇒

a6p

The first solution is therefore given by y1 (x) = a0 z3

∞ ∞   (−1)n 6n (−1)n 3(2n+1) z = a0 z = a0 sin z3 . (2n + 1)! (2n + 1)! n=0 n=0

(b) σ = 0. Equating the general coefficient of zm−1 to zero (with σ = 0) gives m(m − 1)am − 2mam + 9am−6 = 0. Hence the recurrence relation is 9am−6 , m(m − 3) a6p−6 (−1)p a0 9 a6p−6 = − = . =− 6p (6p − 3) 2p (2p − 1) (2p)!

am = − ⇒

a6p

A second solution is thus y2 (x) = a0

∞  (−1)n n=0

(2n)!

z6n = a0 cos z3 .

We see that σ = 0 does, in fact, produce a (different) series solution. This is because the recurrence relation relates an to an+6 and does not involve an+3 ; the relevance here of considering the subscripted index “m + 3” is that “3” is the difference between the two indicial values. We now calculate the Wronskian of the two solutions, y1 = a0 sin z3 and y2 = b0 cos z3 : W (y1 , y2 ) = y1 y2 − y2 y1 = a0 sin z3 (−3b0 z2 sin z3 ) − b0 cos z3 (3a0 z2 cos z3 ) = −3a0 b0 z2 = 0. The fact that the Wronskian is non-zero shows that the two solutions are linearly independent. We can also calculate the Wronskian from the original equation in its standard form, 2 y − y + 9z4 y = 0, z as

  W = C exp −

z

 −2 du = C exp(2 ln z) = Cz2 . u

This is in agreement with the Wronskian calculated from the solutions, as it must be.

108

Series solutions of ordinary differential equations 7.5 Investigate solutions of Legendre’s equation at one of its singular points as follows. (a) Verify that z = 1 is a regular singular point of Legendre’s equation and that the indicial equation for a series solution in powers of (z − 1) has a double root σ = 0. (b) Obtain the corresponding recurrence relation and show that a polynomial solution is obtained if  is a positive integer. (c) Determine the radius of convergence R of the σ = 0 series and relate it to the positions of the singularities of Legendre’s equation.

(a) In standard form, Legendre’s equation reads y −

2z ( + 1) y + y = 0. 1 − z2 1 − z2

This has a singularity at z = 1, but, since ( + 1)(z − 1)2 −2z(z − 1) → 1 and → 0 as z → 1, 1 − z2 1 − z2 i.e. both limits are finite, the point is a regular singular point. We next change the origin to the point z = 1 by writing u = z − 1 and y(z) = f (u). The transformed equation is 2(u + 1) ( + 1) f + y=0 −u(u + 2) −u(u + 2) − u(u + 2)f − 2(u + 1)f + ( + 1)f = 0. f −

or

Thepoint u = 0 is a regular singular point of this equation and so we set f (u) = n uσ ∞ n=0 an u and obtain −u(u + 2)

∞ 

(σ + n)(σ + n − 1)an uσ +n−2

n=0 ∞ ∞   σ +n−1 − 2(u + 1) (σ + n)an u + ( + 1) an uσ +n = 0. n=0

n=0 σ −1

Equating to zero the coefficient of u

gives

−2σ (σ − 1)a0 − 2σ a0 = 0



σ 2 = 0;

i.e. the indicial equation has a double root σ = 0. (b) To obtain the recurrence relation we set the coefficient of um equal to zero for general m: −m(m − 1)am − 2(m + 1)mam+1 − 2mam − 2(m + 1)am+1 + ( + 1)am = 0. Tidying this up gives 2(m + 1)(m + 1)am+1 = [( + 1) − m2 + m − 2m]am , ( + 1) − m(m + 1) ⇒ am+1 = am . 2(m + 1)2

109

Series solutions of ordinary differential equations

From this it is clear that, if  is a positive integer, then a+1 and all further an are zero and that the solution is a polynomial (of degree  ). (c) The limit of the ratio of successive terms in the series is given by      an+1 un+1   u[( + 1) − m(m + 1)]   =  → |u| as m → ∞.  a un    2 2(m + 1) 2 n For convergence this limit needs to be < 1, i.e. |u| < 2. Thus the series converges in a circle of radius 2 centered on u = 0, i.e. on z = 1. The value 2 is to be expected, as it is the distance from z = 1 of the next nearest (actually the only other) singularity of the equation (at z = −1), excluding z = 1 itself. 7.7 The first solution of Bessel’s equation for ν = 0 is J0 (z) =

∞  n=0

(−1)n  z 2n . n!(n + 1) 2

Use the derivative method to show that J0 (z) ln z −

∞  (−1)n n=1

(n!)2

 n   1  z 2n r=1

r

2

is a second (independent) solution.

Bessel’s equation with ν = 0 reads zy + y + zy = 0. The recurrence relations that gave rise to the first solution, J0 (z), were (σ + 1)2 a1 = 0 and (σ + n)2 an + an−2 = 0 for n ≥ 2. Thus, in a general form as a function of σ , the solution is given by  y(σ, z) = a0 zσ 1 −

z2 z4 + − ··· (σ + 2)2 (σ + 2)2 (σ + 4)2  (−1)n z2n + + ··· . [(σ + 2)(σ + 4) . . . (σ + 2n)] 2

Setting σ = 0 reproduces the first solution given above. To obtain a second independent solution, we must differentiate the above expression with respect to σ , before setting σ equal to 0: ∞  da2n (σ ) σ +2n ∂y = ln z J0 (z) + z ∂σ dσ n=1

at σ = 0.

110

Series solutions of ordinary differential equations

Now

   da2n (σ )  (−1)n d = dσ σ =0 dσ [(σ + 2)(σ + 4) . . . (σ + 2n)] 2 σ =0   [. . .] [. . .] (−1)n (−2) [. . .] + + ··· + = [. . .]3 σ +2 σ +4 σ + 2n n n  (−2)(−1) 1 = [. . .]2 r=1 σ + 2r =

n −2(−1)n  1 , 22n (n!)2 r=1 2r

at σ = 0.

Substituting this result, we obtain the second series as  n  ∞  (−1)n  1  z 2n . J0 (z) ln z − (n!)2 r=1 r 2 n=1 This is the form given in the question. 7.9 Find series solutions of the equation y − 2zy − 2y = 0. Identify one of the series as y1 (z) = exp z2 and verify this by direct substitution. By setting y2 (z) = u(z)y1 (z) and solving the resulting equation for u(z), find an explicit form for y2 (z) and deduce that  x ∞  n! 2 2 (2x)2n+1 . e−v dv = e−x 2(2n + 1)! 0 n=0

(a) The origin is an ordinary point equation and so power series solutions will be ∞ of the n possible. Substituting y(z) = n=0 an z gives ∞ 

n(n − 1)an z

n−2

−2

n=0

∞ 

nan z − 2

n=0

Equating to zero the coefficient of z am =

m−2

n

∞ 

an zn = 0.

n=0

yields the recurrence relation

2m − 2 2 am−2 = am−2 . m(m − 1) m

The solution with a0 = 1 and a1 = 0 is therefore y1 (z) = 1 + =

22 z 4 2n z2n 2z2 + + ··· + n + ··· 2 (2)(4) 2 n!

∞  z2n n=0

n!

= exp z2 .

Putting this result into the original equation, (4z2 + 2) exp z2 − 2z 2z exp z2 − 2 exp z2 = 0, shows directly that it is a valid solution.

111

Series solutions of ordinary differential equations

The solution with a0 = 0 and a1 = 1 takes the form y2 (z) = z + =

22 z5 2n 2n n! z2n+1 2z3 + + ··· + + ··· 3 (3)(5) (2n + 1)!

∞  n! (2z)2n+1 n=0

2(2n + 1)!

.

(b) We now set y2 (z) = u(z)y1 (z) and substitute it into the original equation. As they must, the terms in which u is undifferentiated cancel and leave u exp z2 + 2u (2z exp z2 ) − 2zu exp z2 = 0. It follows that u = −2z u



u = Ae−z



2



u(x) = A

x

e−v dv. 2

Hence, setting the two derived forms for a second solution equal to each other, we have ∞  n! (2x)2n+1 n=0

2(2n + 1)!

x2



= y2 (x) = y1 (x)u(x) = e A

x

e−v dv. 2

For arbitrary small x, only the n = 0 term in the series is significant and takes the value x 1 dv = Ax. Thus A = 1 and the equality 2x/2 = x, whilst the integral is A 

x

e−v dv = e−x 2

0

2

∞  n! (2x)2n+1 n=0

2(2n + 1)!

holds for all x. 7.11 For the equation y + z−3 y = 0, show that the origin becomes a regular singular point if the independent is changed from z to x = 1/z. Hence find a series solution of the form  variable −n y1 (z) = ∞ 0 an z . By setting y2 (z) = u(z)y1 (z) and expanding the resulting expression for du/dz in powers of z−1 , show that y2 (z) is a second solution with asymptotic form    ln z y2 (z) = c z + ln z − 12 + O , z where c is an arbitrary constant.

With the equation in its original form, it is clear that, since z2 /z3 → ∞ as z → 0, the origin is an irregular singular point. However, if we set 1/z = ξ and y(z) = Y (ξ ), with dξ 1 = − 2 = −ξ 2 dz z



d d = −ξ 2 , dz dξ

112

Series solutions of ordinary differential equations

then

  d 2 dY −ξ −ξ + ξ 3 Y = 0, dξ dξ d 2Y dY + ξ Y = 0, ξ 2 2 + 2ξ dξ dξ 2 1 Y + Y + Y = 0. ξ ξ 2

By inspection, ξ = 0 is a regular singular point of this equation, and its indicial equation is σ (σ − 1) + 2σ = 0



σ = 0, −1.

We start with the larger root, σ = 0, as this is “guaranteed” to give a valid series solution n and assume a solution of the form Y (ξ ) = ∞ n=0 an ξ , leading to ∞ 

n(n − 1)an ξ

n−1

+2

n=0

∞ 

nan ξ

n−1

+

n=0

Equating to zero the coefficient of ξ

m−1

∞ 

an ξ n = 0.

n=0

gives the recurrence relation

−am−1 (−1)m ⇒ am = a0 m(m + 1) (m + 1) (m!)2 and the series solution in inverse powers of z, am =

y1 (z) = a0

∞  n=0

(−1)n . (n + 1) (n!)2 zn

To find the second solution we set y2 (z) = f (z)y1 (z). As usual (and as intended), all terms with f undifferentiated vanish when this is substituted in the original equation. What is left is 0 = f (z)y1 (z) + 2f (z)y1 (z), which on rearrangement yields f 2y = − 1. f y1 This equation, although it contains a second derivative, is in fact only a first-order equation (for f ). It can be integrated directly to give ln f = −2 ln y1 + c. After exponentiation, this equation can be written as  −2 A 1 df 1 A = 2 + − ··· = 2 1− dz 2 × 12 z 3 × 22 z2 y1 (z) a0    1 1 A , = 2 1+ +O 2 z z a0 where A = ec .

113

Series solutions of ordinary differential equations

Hence, on integrating a second time, one obtains    A 1 f (z) = 2 z + ln z + O , z a0 which in turn implies

     A 1 1 1 − · · · a + z + ln z + O 1 − 0 z 2z 12z2 a02    ln z 1 . = c z + ln z − + O 2 z

y2 (z) =

This establishes the asymptotic form of the second solution. 7.13 The origin is an ordinary point of the Chebyshev equation, (1 − z2 )y − zy + m2 y = 0,  n which therefore has series solutions of the form zσ ∞ 0 an z for σ = 0 and σ = 1. (a) Find the recurrence relationships for the an in the two cases and show that there exist polynomial solutions Tm (z): (i) for σ = 0, when m is an even integer, the polynomial having 12 (m + 2) terms; (ii) for σ = 1, when m is an odd integer, the polynomial having 12 (m + 1) terms. (b) Tm (z) is normalized so as to have Tm (1) = 1. Find explicit forms for Tm (z) for m = 0, 1, 2, 3. (c) Show that the corresponding non-terminating series solutions Sm (z) have as their first few terms   9 1 S0 (z) = a0 z + z3 + z5 + · · · , 3! 5!   3 4 1 2 S1 (z) = a0 1 − z − z − · · · , 2! 4!   15 3 S2 (z) = a0 z − z3 − z5 − · · · , 3! 5!   9 2 45 4 S3 (z) = a0 1 − z + z + · · · . 2! 4!

(a) (i) If, for σ = 0, y(z) = of zr in (1 − z2 )

∞  n=0

∞ n=0

an zn with a0 = 0, the condition for the coefficient

n(n − 1)an zn−2 − z

∞  n=0

nan zn−1 + m2

∞ 

an zn

n=0

to be zero is that (r + 2)(r + 1)ar+2 − r(r − 1)ar − rar + m2 ar = 0, r 2 − m2 ⇒ ar+2 = ar . (r + 2)(r + 1) This relation relates ar+2 to ar and so to a0 if r is even. For ar+2 to vanish, in this case, requires that r = m, which must therefore be an even integer. The non-vanishing coefficients will be a0 , a2 , . . . , am , i.e. 12 (m + 2) of them in all.

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Series solutions of ordinary differential equations

(ii) If, for σ = 1, y(z) = of zr+1 in

∞ n=0

an zn+1 with a0 = 0, the condition for the coefficient

∞ ∞ ∞    n−1 n 2 (1 − z ) (n + 1)nan z −z (n + 1)an z + m an zn+1 2

n=0

n=0

n=0

to be zero is that (r + 3)(r + 2)ar+2 − (r + 1)rar − (r + 1)ar + m2 ar = 0, (r + 1)2 − m2 ⇒ ar+2 = ar . (r + 3)(r + 2) This relation relates ar+2 to ar and so to a0 if r is even. For ar+2 to vanish, in this case, requires that r + 1 = m, which must therefore be an odd integer. The non-vanishing coefficients will be, as before, a0 , a2 , . . . , am−1 , i.e. 12 (m + 1) of them in all. (b) For m = 0, T0 (z) = a0 . With the given normalization, a0 = 1 and T0 (z) = 1. For m = 1, T1 (z) = a0 z. The required normalization implies that a0 = 1 and so T0 (z) = z. For m = 2, we need the recurrence relation in (a)(i). This shows that a2 =

02 − 22 a0 = −2a0 (2)(1)



T2 (z) = a0 (1 − 2z2 ).

With the given normalization, a0 = −1 and T2 (z) = 2z2 − 1. For m = 3, we use the recurrence relation in (a)(ii) and obtain   4z3 12 − 3 2 4 a2 = a0 = − a0 ⇒ T3 (z) = a0 z − . (3)(2) 3 3 For the required normalization, we must have a0 = − 13 and consequently that T3 (z) = 4z3 − 3z. (c) The non-terminating series solutions Sm (z) arise when σ = 0 but m is an odd integer and when σ = 1 with m an even integer. We take each in turn and apply the appropriate recurrence relation to generate the coefficients. (i) σ = 0, m = 1, using the (a)(i) recurrence relation: a2 = Hence,

0−1 1 a0 = − a0 , (2)(1) 2!

a4 =

4−1 3 a2 = − a0 . (4)(3) 4!

  1 2 3 4 S1 (z) = a0 1 − z − z − · · · . 2! 4!

(ii) σ = 0, m = 3, using the (a)(i) recurrence relation: a2 = Hence,

0−9 9 a0 = − a0 , (2)(1) 2!

a4 =

4−9 45 a2 = a0 . (4)(3) 4!

  9 2 45 4 S3 (z) = a0 1 − z + z + · · · . 2! 4!

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Series solutions of ordinary differential equations

(iii) σ = 1, m = 0, using the (a)(ii) recurrence relation: a2 =

1−0 1 a0 = a0 , (3)(2) 3!

Hence,

 S0 (z) = a0

a4 =

9−0 9 a2 = a0 . (5)(4) 5!

1 9 z + z3 + z5 + · · · 3! 5!

 .

(iv) σ = 1, m = 2, using the (a)(ii) recurrence relation: a2 =

1−4 3 a0 = − a0 , (3)(2) 3!

Hence,

 S2 (z) = a0

a4 =

9−4 15 a2 = − a0 . (5)(4) 5!

3 15 z − z3 − z5 − · · · 3! 5!

 .

8

Eigenfunction methods for differential equations

8.1 By considering h|h, where h = f + λg with λ real, prove that, for two functions f and g, f |f g|g ≥ 14 [f |g + g|f ]2 . The function y(x) is real and positive for all x. Its Fourier cosine transform y˜c (k) is defined by  ∞ y˜c (k) = y(x) cos(kx) dx, −∞

and it is given that y˜c (0) = 1. Prove that y˜c (2k) ≥ 2[y˜c (k)]2 − 1.

For any |h we have that h|h ≥ 0, with equality only if |h = |0. Hence, noting that λ is real, we have 0 ≤ h|h = f + λg|f + λg = f |f  + λg|f  + λf |g + λ2 g|g. This equation, considered as a quadratic inequality in λ, states that the corresponding quadratic equation has no real roots. The condition for this (“b2 < 4ac”) is given by [g|f  + f |g]2 ≤ 4f |f g|g,

(∗)

from which the stated result follows immediately. Note that g|f  + f |g is real and its square is therefore non-negative. The given datum is equivalent to  ∞  ∞ y(x) cos(0x) dx = y(x) dx. 1 = y˜c (0) = −∞

Now consider

−∞

 y˜c (2k) = =2 ⇒

y˜c (2k) + 1 = 2



y(x) cos(2kx) dx −∞  ∞

−∞ ∞

 y(x) cos kx − 2



y(x) dx, −∞

y(x) cos2 kx.

−∞

In order to use (∗), we need to choose for f (x) and g(x) functions whose product will form the integrand defining y˜c (k). With this in mind, we take f (x) = y 1/2 (x) cos kx and 116

117

Eigenfunction methods for differential equations

g(x) = y 1/2 (x); we may do this since y(x) > 0 for all x. Making these choices gives 2  ∞  ∞  ∞  ∞ 2 y cos kx dx + y cos kx dx ≤ 4 y cos kx dx y dx, −∞



−∞ ∞

2

2y cos kx dx −∞

≤4

4y˜c2 (k) ≤ 4 Thus,

 y˜c (2k) + 1 = 2



−∞

−∞ ∞

−∞



−∞ ∞

y cos2 kx dx × 1, y cos2 kx dx.

−∞

y(x) cos2 kx ≥ 2[y˜c (k)]2

and hence the stated result. 8.3 Consider the real eigenfunctions yn (x) of a Sturm–Liouville equation (py ) + qy + λρy = 0,

a ≤ x ≤ b,

in which p(x), q(x) and ρ(x) are continuously differentiable real functions and p(x) does not change sign in a ≤ x ≤ b. Take p(x) as positive throughout the interval, if necessary by changing the signs of all eigenvalues. For a ≤ x1 ≤ x2 ≤ b, establish the identity  x2  x (λn − λm ) ρyn ym dx = yn p ym − ym p yn x21 . x1

Deduce that if λn > λm then yn (x) must change sign between two successive zeros of ym (x). [The reader may find it helpful to illustrate this result by sketching the first few eigenfunctions of the system y + λy = 0, with y(0) = y(π) = 0, and the Legendre polynomials Pn (z) for n = 2, 3, 4, 5.]

The function p (x) does not change sign in the interval a ≤ x ≤ b; we take it as positive, multiplying the equation all through by −1 if necessary. This means that the weight function ρ can still be taken as positive, but that we must consider all possible functions for q(x) and eigenvalues λ of either sign. We start with the eigenvalue equation for yn (x), multiply it through by ym (x) and then integrate from x1 to x2 . From this result we subtract the same equation with the roles of n and m reversed, as follows. The integration limits are omitted until the explicit integration by parts is carried through:    ym (p yn ) dx + ym q yn dx + ym λn ρyn dx = 0,    yn (p ym ) dx + yn q ym dx + yn λm ρym dx = 0,    ym (p yn ) − yn (p ym ) dx + (λn − λm ) ym ρyn dx = 0,  x x   ym p yn x21 − ym p yn dx − yn p ym x21   + yn p ym dx + (λn − λm ) ym ρyn dx = 0.

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Eigenfunction methods for differential equations

Hence

 (λn − λm )

 x ym ρyn dx = yn p ym − ym p yn x21 .

(∗)

Now, in this general result, take x1 and x2 as successive zeros of ym (x), where m is determined by λn > λm (after the signs have been changed, if that was necessary). Clearly the sign of ym (x) does not change in this interval; let it be α. It follows that the sign of ym (x1 ) is also α, whilst that of ym (x2 ) is −α. In addition, the second term on the RHS of (∗) vanishes at both limits, as ym (x1 ) = ym (x2 ) = 0. Let us now suppose that the sign of yn (x) does not change in this same interval and is always β. Then the sign of the expression on the LHS of (∗) is (+1)(α)(+1)β = αβ. The first (+1) appears because λn > λm . The signs of the upper- and lower-limit contributions of the remaining term on the RHS of (∗) are β(+1)(−α) and (−1)β(+1)α, respectively, the additional factor of (−1) in the second product arising from the fact that the contribution comes from a lower limit. The contributions at both limits have the same sign, −αβ, and so the sign of the total RHS must also be −αβ. This contradicts, however, the sign of +αβ found for the LHS. It follows that it was wrong to suppose that the sign of yn (x) does not change in the interval; in other words, a zero of yn (x) does appear between every pair of zeros of ym (x). 8.5 Use the properties of Legendre polynomials to solve the following problems. (a) Find the solution of (1 − x 2 )y − 2xy + by = f (x) that is valid in the range −1 ≤ x ≤ 1 and finite at x = 0, in terms of Legendre polynomials. (b) Find the explicit solution if b = 14 and f (x) = 5x 3 . Verify it by direct substitution. [Explicit forms for the Legendre polynomials can be found in any textbook. In Mathematical Methods for Physics and Engineering, 3rd edition, they are given in Subsection 18.1.1.]

(a) The LHS of the givenequation is the same as that of Legendre’s equation and 2 so we substitute y(x) = ∞ n=0 an Pn (x) and use the fact that (1 − x )Pn − 2xPn = −n(n + 1)Pn . This results in ∞ 

an [b − n(n + 1)]Pn = f (x).

n=0

Now, using the mutual orthogonality and normalization of the Pn (x), we multiply both sides by Pm (x) and integrate over x:  1 2 an [b − n(n + 1)] δmn f (z)Pm (z) dz, = 2m + 1 −1 n=0  1 2m + 1 ⇒ am = f (z)Pm (z) dz. 2[b − m(m + 1)] −1

∞ 

This gives the coefficients in the solution y(x).

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Eigenfunction methods for differential equations

(b) We now express f (x) in terms of Legendre polynomials,  f (x) = 5x 3 = 2 12 (5x 3 − 3x) + 3[x] = 2P3 (x) + 3P1 (x), and conclude that, because of the mutual orthogonality of the Legendre polynomials, only a3 and a1 in the series solution will be non-zero. To find them we need to evaluate  1 4 2 = ; f (z)P3 (z) dz = 2 2(3) + 1 7 −1 1 similarly, −1 f (z)P1 (z) dz = 3 × (2/3) = 2. Inserting these values gives a3 =

4 7 =1 2(14 − 12) 7

and a1 =

1 3 2= . 2(14 − 2) 4

Thus the solution is y(x) =

1 1 1 5(2x 3 − x) P1 (x) + P3 (x) = x + (5x 3 − 3x) = . 4 4 2 4

Check: 60x 30x 2 − 5 140x 3 − 70x − 2x + = 5x 3 , 4 4 4 60x − 60x 3 − 60x 3 + 10x + 140x 3 − 70x = 20x 3 ,

(1 − x 2 ) ⇒ which is satisfied.

8.7 Consider the set of functions, {f (x)}, of the real variable x defined in the interval −∞ < x < ∞, that → 0 at least as quickly as x −1 , as x → ±∞. For unit weight function, determine whether each of the following linear operators is Hermitian when acting upon {f (x)}: (a)

d + x; dx

(b) − i

d + x2; dx

(c) ix

d ; dx

(d) i

d3 . dx 3

For an operator L to be Hermitian over the given range with respect to a unit weight function, the equation  ∞ ∗  ∞ ∗ ∗ f (x)[Lg(x)] dx = g (x)[Lf (x)] dx (∗) −∞

−∞

must be satisfied for general functions f and g. d (a) For L = + x, the LHS of (∗) is dx    ∞  ∞  ∞ ∞  dg df ∗ f ∗ (x) f ∗ xg dx + xg dx = f ∗ g −∞ − g dx + dx dx −∞ −∞ −∞  ∞  ∞ df ∗ ∗ =0− f xg dx. g dx + −∞ dx −∞

120

Eigenfunction methods for differential equations

The RHS of (∗) is 

∞ −∞





df + xf g (x) dx ∗



∗ dx

 =



g 

∗ df

dx

−∞

∗ dx



df ∗ dx + = g dx −∞

 +









∗

g xf dx −∞

gxf ∗ dx.

−∞

Since the sign of the first term differs in the two expressions, the LHS = RHS and L is not Hermitian. It will also be apparent that purely multiplicative terms in the operator, such as x or x 2 , will always be Hermitian; thus we can ignore the x 2 term in part (b). (b) As explained above, we need only consider 





dg f (x) −i dx −∞ ∗





∞ df ∗ dx = −if g −∞ + i g dx −∞ dx  ∞ df ∗ g dx =0+i −∞ dx







and 





−∞

  ∗  ∞ df df ∗ g dx = i dx. g ∗ (x) −i dx dx −∞

d d is Hermitian, as is L = −i + x2. These are equal, and so L = −i dx dx d (c) For L = ix , the LHS of (∗) is dx 





dg f (x) ix dx −∞ ∗



 ∞ df ∗ dx = ixf g −∞ − i g dx − i x f ∗ g dx dx −∞ −∞  ∞  ∞ df ∗ g dx − i x f ∗ g dx. =0−i dx −∞ −∞ 









The RHS of (∗) is given by 







g (x)ix −∞



df dx



∗ dx

 = −i



gx −∞

df ∗ dx. dx

∞ Since, in general, −i −∞ fg ∗ dx = 0, the two sides are not equal; therefore L is not Hermitian. d3 d (d) Since L = i 3 is the cube of the operator −i , which was shown in part (b) to dx dx be Hermitian, it is expected that L is Hermitian. This can be verified directly as follows.

121

Eigenfunction methods for differential equations

The LHS of (∗) is given by   ∞  ∞ 3 2 ∞ df ∗ d 2 g ∗d g ∗d g i f dx = if − i dx 2 dx 3 dx 2 −∞ −∞ −∞ dx dx  ∗   ∞ 2 ∗ df dg ∞ d f dg =0−i +i dx 2 dx dx dx −∞ −∞ dx  2 ∗ ∞  ∞ 3 ∗ d f d f =0+i g −i g dx 2 3 dx −∞ dx −∞ ∗  ∞ 3 ∗d f ig dx = RHS of (∗). =0+ dx 3 −∞ Thus L is confirmed as Hermitian. 8.9 Find an eigenfunction expansion for the solution with boundary conditions y(0) = y(π) = 0 of the inhomogeneous equation d 2y + κy = f (x), dx 2 where κ is a constant and

 f (x) =

x π −x

The eigenfunctions of the operator L =

0 ≤ x ≤ π/2, π/2 < x ≤ π.

d2 + κ are obviously dx 2

yn (x) = An sin nx + Bn cos nx, with corresponding eigenvalues λn = n2 − κ. The boundary conditions, y(0) = y(π) = 0, require that n is a positive integer and that Bn = 0, i.e. ' 2 sin nx, yn (x) = An sin nx = π where An (for n ≥ 1) has been chosen so that the eigenfunctions are normalized over the interval x = 0 to x = π. Since L is Hermitian on the range 0 ≤ x ≤ π, the eigenfunctions are also mutually orthogonal, and so the yn (x) form an orthonormal set. If the required solution is y(x) = n an yn (x), then direct substitution yields the result ∞  (κ − n2 )an yn (x) = f (x). n=1

Following the usual procedure for analysis using sets of orthonormal functions, this implies that  π 1 f (z)ym (z) dz am = κ − m2 0

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Eigenfunction methods for differential equations

and, consequently, that y(x) =

∞ 

'

n=1

2 sin nx π κ − n2

It only remains to evaluate  π In = sin(nx)f (x) dx 0   π/2 x sin nx dx + =

'

π



2 π

π

f (z) sin(nz) dz. 0

(π − x) sin nx dx

π/2

0

  π/2 cos nx −x cos nx π/2 dx + = n n 0 0    π −(π − x) cos nx π (−1) cos nx + + dx n n π/2 π/2 " sin nx #π/2 " sin nx #π π cos(nπ/2) − (1 − 1) + =− 2 n n2 0 n2 π/2 (n−1)/2 (−1) =0+ (1 + 1) for odd n and = 0 for even n. n2 

Thus, y(x) =

4  (−1)(n−1)/2 sin nx π n odd n2 (κ − n2 )

is the required solution. 8.11 The differential operator L is defined by Ly = −

d dx

 ex

dy dx

 − 14 ex y.

Determine the eigenvalues λn of the problem Lyn = λn ex yn

0 < x < 1,

with boundary conditions dy + 12 y = 0 at x = 1. dx (a) Find the corresponding unnormalized yn , and also a weight function ρ(x) with respect to which the yn are orthogonal. Hence, select a suitable normalization for the yn . (b) By making an eigenfunction expansion, solve the equation y(0) = 0,

Ly = −ex/2 ,

0 < x < 1,

subject to the same boundary conditions as previously.

When written out explicitly, the eigenvalue equation is   d x dy − e − 14 ex y = λex y, dx dx

(∗)

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Eigenfunction methods for differential equations

or, on differentiating out the product,   ex y + ex y + λ + 14 ex y = 0. The auxiliary equation is   m2 + m + λ + 14 = 0 The general solution is thus given by y(x) = Ae−x/2 cos





√ m = − 12 ± i λ.

λx + Be−x/2 sin

√ λx,

with the condition y(0) = 0 implying that A = 0. The other boundary condition requires that, at x = 1, √ √ √ √ − 12 Be−x/2 sin λx + λBe−x/2 cos λx + 12 Be−x/2 sin λx = 0, √ i.e. that cos λ = 0 and hence that λ = (n + 12 )2 π 2 for non-negative integral n. (a) The unnormalized eigenfunctions are   yn (x) = Bn e−x/2 sin n + 12 πx and (∗) is in Sturm–Liouville form. However, although yn (0) = 0, the values at the upper  1 limit in ym p yn 0 are yn (1) = Bn e−1/2 (−1)n , p(1) = e1 and ym (1) = − 12 Bm e−1/2 (−1)m . 1  Consequently, ym p yn 0 = 0 and SL theory cannot be applied. We therefore have to find a suitable weight function ρ(x) by inspection. Given the general form of the eigenfunctions, ρ has to be taken as ex , with the orthonormality integral taking the form  1 ρ(x)yn (x)ym∗ (x) dx Inm = 0  1     ex e−x/2 sin n + 12 πx e−x/2 sin m + 12 πx dx = Bn Bm 0  0 for m = n, = 1 B B for m = n. n m 2 √ It is clear that a suitable normalization  is Bn = 2 for all n. (b) We write the solution as y(x) = ∞ n=0 an yn (x), giving as the equation to be solved −ex/2 = Ly = L = =

∞ 

an yn (x)

n=0 ∞ 

an [λn ρ(x)yn (x)]

n=0 ∞ 

 2   √ an n + 12 π 2 ex 2e−x/2 sin n + 12 πx

n=0



−1 =

∞  n=0

 2 √   an n + 12 π 2 2 sin n + 12 πx .

124

Eigenfunction methods for differential equations

  After multiplying both sides of this equation by sin m + 12 πx and integrating from 0 to 1, we obtain  1  1     −1 am sin2 m + 12 πx dx =  sin m + 12 πx dx,  √ 2 0 m + 12 π 2 2 0  1   −1 am = sin m + 12 πx dx 2 √ 1 2 m + 2 π2 2 0    1 cos m + 12 πx 1   , =  2 √ m + 12 π m + 12 π 2 2 0 √ 2 am = −  3 . m + 12 π 3 √ Substituting this result into the assumed expansion, and recalling that Bn = 2, gives as the solution ∞    2 e−x/2 sin n + 12 πx. y(x) = −   1 3 3 n=0 n + 2 π 8.13 By substituting x = exp t, find the normalized eigenfunctions yn (x) and the eigenvalues λn of the operator L defined by Ly = x 2 y + 2xy + 14 y,

with y(1) = y(e) = 0. Find, as a series



1 ≤ x ≤ e,

an yn (x), the solution of Ly = x −1/2 .

Putting x = et and y(x) = u(t) with u(0) = u(1) = 0, d dx d = et ⇒ = e−t dt dx dt and the eigenvalue equation becomes   du 1 2t −t d −t du e + 2et e−t + u = λu, e e dt dt dt 4   du 1 d 2 u du + 2 + − λ = 0. − dt 2 dt dt 4 The auxiliary equation to this constant-coefficient linear equation for u is √ m2 + m + ( 14 − λ) = 0 ⇒ m = − 12 ± λ, leading to

 √ √  u(t) = e−t/2 Ae λ t + Be− λ t .

In view of the requirement that u vanishes at two different values of t (one of which is t = 0), we need λ < 0 and u(t) to take the form √ √ u(t) = Ae−t/2 sin −λ t with −λ 1 = nπ, i.e. λ = −n2 π 2 ,

125

Eigenfunction methods for differential equations

where n is an integer. Thus un (t) = An e−t/2 sin nπt

An or, in terms of x, yn (x) = √ sin(nπ ln x). x

Normalization requires that  1= 1

e

A2n 2 sin (nπ ln x) dx = x



1 0

A2n sin2 (nπt) dt = 12 A2n



An =



2.

To solve 1 Ly = x 2 y + 2xy + 14 y = √ , x we set y(x) =

∞ n=0

an yn (x). Then the equation becomes

√ 2 1 Ly = an (−n π )yn (x) = −n π an √ sin(nπ ln x) = √ . x x n=0 n=0 ∞ 

2

2

∞ 

2

2

Multiplying through by ym (x) and integrating, as with ordinary Fourier series, 

e 1

1 2an sin(nπ ln x) sin(mπ ln x) dx = − 2 2 x nπ

 1

e

√ 2 sin(mπ ln x) dx. x

The LHS of this equation is the normalization integral just considered and has the value am δmn . Thus √  e sin(mπ ln x) 2 dx m2 π 2 1 x  √  2 − cos(mπ ln x) e =− 2 2 mπ mπ 1 √ 2 = − 3 3 [1 − (−1)m ] ⎧ m π√ ⎨ 2 2 − 3 3 for m odd, = mπ ⎩ 0 for m even.

am = −

The explicit solution is therefore y(x) = −

∞ 4  sin[(2p + 1)π ln x] . √ π 3 p=0 (2p + 1)3 x

126

Eigenfunction methods for differential equations

8.15 In the quantum mechanical study of the scattering of a particle by a potential, a Born-approximation solution can be obtained in terms of a function y(r) that satisfies an equation of the form (−∇ 2 − K 2 )y(r) = F (r). Assuming that yk (r) = (2π)−3/2 exp(ik · r) is a suitably normalized eigenfunction of −∇ 2 corresponding to eigenvalue k 2 , find a suitable Green’s function GK (r, r ). By taking the direction of the vector r − r as the polar axis for a k-space integration, show that GK (r, r ) can be reduced to  ∞ w sin w 1 dw, 4π 2 |r − r | −∞ w2 − w02 where w0 = K|r − r |. [This integral can be evaluated using contour integration and gives the Green’s function explicitly as (4π|r − r |)−1 exp(iK|r − r |).]

Given that yk (r) = (2π)−3/2 exp(ik · r) satisfies −∇ 2 yk (r) = k 2 yk (r), it follows that (−∇ 2 − K 2 )yk (r) = (k 2 − K 2 )yk (r). Thus the same functions are suitable eigenfunctions for the extended operator, but with different eigenvalues. Its Green’s function is therefore (from the general expression for Green’s functions in terms of eigenfunctions)  1 GK (r, r ) = yk (r)yk∗ (r ) dk λ  1 exp(ik · r) exp(−ik · r ) = dk. (2π)3 k2 − K 2 We carry out the three-dimensional integration in k-space using the direction r − r as the polar axis (and denote r − r by R). The azimuthal integral is immediate. The remaining two-dimensional integration is as follows:  ∞ π exp(ik · R) 1 GK (r, r ) = 2πk 2 sin θk dθk dk 2 − K2 (2π)3 0 k 0  ∞ π exp(ikR cos θk ) 2 1 k sin θk dθk dk = 2 (2π) 0 k2 − K 2 0  ∞ 1 exp(ikR) − exp(−ikR) 2 k dk = 2 (2π) 0 ikR(k 2 − K 2 )  ∞ k sin kR 1 dk = 2 2π R 0 k 2 − K 2

127

Eigenfunction methods for differential equations

1 = 2π 2 R =

1 4π 2 R

 

∞ 0 ∞ −∞

w sin w dw, w2 − w02

where w = kR and w0 = kR,

w sin w dw. w2 − w02

Here, the final line is justified by noting that the integrand is an even function of the integration variable w.

9

Special functions

9.1 Use the explicit expressions  1 , Y00 = 4π  3 Y1±1 = ∓ 8π sin θ exp(±iφ),  15 Y2±1 = ∓ 8π sin θ cos θ exp(±iφ),

Y10 = Y20 = Y2±2 =

  

3 4π

cos θ,

5 (3 cos2 16π 15 32π

θ − 1),

sin2 θ exp(±2iφ),

to verify for  = 0, 1, 2 that     m Y (θ, φ)2 = 2 + 1  4π m=−

and so is independent of the values of θ and φ. This is true for any , but a general proof is more involved. This result helps to reconcile intuition with the apparently arbitrary choice of polar axis in a general quantum mechanical system.

We first note that, since every term is the square of a modulus, factors of the form exp(±miφ) never appear in the sums. For each value of , let us denote the sum by S . For  = 0 and  = 1, we have S0 =

0    m Y (θ, φ)2 = 1 , 0 4π m=0

1    m Y (θ, φ)2 = 3 cos2 θ + 2 3 sin2 θ = 3 . S1 = 1 4π 8π 4π m=−1

For  = 2, the summation is more complicated but reads 2    m Y (θ, φ)2 S2 = 2 m=−2

5 15 15 (3 cos2 θ − 1)2 + 2 sin2 θ cos2 θ + 2 sin4 θ 16π 8π 32π 5 (9 cos4 θ − 6 cos2 θ + 1 + 12 sin2 θ cos2 θ + 3 sin4 θ) = 16π

=

128

129

Special functions

5 [6 cos4 θ − 6 cos2 θ + 1 + 6 sin2 θ cos2 θ + 3(cos2 θ + sin2 θ)2 ] 16π 5 5 [6 cos2 θ(− sin2 θ) + 1 + 6 sin2 θ cos2 θ + 3] = . = 16π 4π =

All three sums are independent of θ and φ, and are given by the general formula (2 + 1)/4π. It will, no doubt, be noted that 2 + 1 is the number of terms in S , i.e. the number of m values, and that 4π is the total solid angle subtended at the origin by all space. 9.3 Use the generating function for the Legendre polynomials Pn (x) to show that  1 (2n)! P2n+1 (x) dx = (−1)n 2n+1 2 n!(n + 1)! 0 and that, except for the case n = 0,



1

P2n (x) dx = 0.

0

1 Denote 0 Pn (x) dx by an . From the generating function for the Legendre polynomials, we have ∞

 1 = Pn (x)hn . 2 1/2 (1 − 2xh + h ) n=0 Integrating this definition with respect to x gives  ∞  1  dx = Pn (x) dx hn , 2 )1/2 (1 − 2xh + h 0 0 n=0  ∞ 2 1/2 1  −(1 − 2xh + h ) = an hn , h 0 n=0 

1



 1 an hn . [(1 + h2 )1/2 − 1 + h] = h n=0 Now expanding (1 + h2 )1/2 using the binomial theorem yields  ∞  1 1+ an h = h n=0 m=1

∞ 

n

 1/2

2m

Cm h

−1+h

=1+

∞ 

1/2

Cm h2m−1 .

m=1

Comparison of the coefficients of hn on the two sides of the equation shows that all a2r are zero except for a0 = 1. For n = 2r + 1 we need 2m − 1 = n = 2r + 1, i.e. m = r + 1, and the value of a2r+1 is 1/2 Cr+1 .

130

Special functions

Now, the binomial coefficient 1/2 Cm can be written as      1 1 − 1 12 − 2 · · · 12 − m + 1 1/2 2 2 , Cm = m! 1(1 − 2)(1 − 4) · · · (1 − 2m + 2) = 2m m! (1)(1)(3) · · · (2m − 3) = (−1)m−1 2m m! (2m − 2)! = (−1)m−1 m m−1 2 m! 2 (m − 1)! (2m − 2)! = (−1)m−1 2m−1 . 2 m! (m − 1)! Thus, setting m = r + 1 gives the value of the integral a2r+1 as a2r+1 =

1/2

Cr+1 = (−1)r

22r+1

(2r)! , (r + 1)! r!

as stated in the question. 9.5 The Hermite polynomials Hn (x) may be defined by (x, h) = exp(2xh − h2 ) =

∞  1 Hn (x)hn . n! n=0

Show that ∂ 2 ∂ ∂ + 2h = 0, − 2x ∂x 2 ∂x ∂h and hence that the Hn (x) satisfy the Hermite equation, y − 2xy + 2ny = 0, where n is an integer ≥ 0. Use  to prove that (a) Hn (x) = 2nHn−1 (x), (b) Hn+1 (x) − 2xHn (x) + 2nHn−1 (x) = 0.

With (x, h) = exp(2xh − h2 ) =

∞  1 Hn (x)hn , n! n=0

we have ∂ = 2h, ∂x It then follows that

∂ = (2x − 2h), ∂h

∂ 2 = 4h2 . ∂x 2

∂ ∂ ∂ 2 + 2h = (4h2 − 4hx + 4hx − 4h2 ) = 0. − 2x 2 ∂x ∂x ∂h

131

Special functions

Substituting the series form into this result gives  ∞   1 2x 2n Hn − Hn + hn = 0, n! n! n! n=0 ⇒

Hn − 2xHn + 2nHn = 0.

This is the equation satisfied by Hn (x), as stated in the question. (a) From the first relationship derived above, we have that ∂ = 2h, ∂x ∞ ∞   1 1 n Hn (x)h = 2h Hn (x)hn , n! n! n=0 n=0 1 2 Hm = Hm−1 , from the coefficients of hm . m! (m − 1)! Hn (x) = 2nHn−1 (x).

⇒ Hence,

(b) Differentiating result (a) and then applying it again yields = 2n 2(n − 1)Hn−2 . Hn = 2nHn−1

Using this in the differential equation satisfied by the Hn , we obtain 4n(n − 1)Hn−2 − 2x 2nHn−1 + 2nHn = 0. This gives Hn+1 (x) − 2xHn (x) + 2nHn−1 (x) = 0 after dividing through by 2n and changing n → n + 1. 9.7 For the associated Laguerre polynomials, carry out the following: (a) Prove the Rodrigues’ formula Lm n (x) =

ex x −m d n n+m −x (x e ), n! dx n

taking the polynomials to be defined by Lm n (x) =

n  (−1)k k=0

(n + m)! xk . k!(n − k)!(k + m)!

(b) Prove the recurrence relations m m (n + 1)Lm n+1 (x) = (2n + m + 1 − x)Ln (x) − (n + m)Ln−1 (x), m m x(Lm n ) (x) = nLn (x) − (n + m)Ln−1 (x),

but this time taking the polynomial as defined by m Lm n (x) = (−1)

or the generating function.

dm Ln+m (x) dx m

132

Special functions

(a) It is most convenient to evaluate the nth derivative directly, using Leibnitz’ theorem. This gives Lm n (x)

n d r n+m d n−r −x n! ex x −m  = (x ) n−r (e ) n! r=0 r!(n − r)! dx r dx x −m

=e x

n  r=0

(n + m)! 1 x n+m−r (−1)n−r e−x r!(n − r)! (n + m − r)!

n  (n + m)! (−1)n−r x n−r . = r!(n − r)! (n + m − r)! r=0

Relabeling the summation using the new index k = n − r, we immediately obtain Lm n (x)

n  = (−1)k k=0

(n + m)! xk, k!(n − k)!(k + m)!

which is as given in the question. (b) The first recurrence relation can be proved using the generating function for the associated Laguerre functions: ∞

G(x, h) =

 e−xh/(1−h) n = Lm n (x)h . (1 − h)m+1 n=0

Differentiating the second equality with respect to h, we obtain (m + 1)(1 − h) − x −xh/(1−h)  m n−1 e = nLn h . (1 − h)m+3 Using the generating function for a second time, we may rewrite this as   n 2 n−1 . nLm [(m + 1)(1 − h) − x] Lm n h = (1 − h) nh Equating the coefficients of hn now yields m m m m m (m + 1)Lm n − (m + 1)Ln−1 − xLn = (n + 1)Ln+1 − 2nLn + (n − 1)Ln−1 ,

which can be rearranged and simplified to give the first recurrence relation. The second result is most easily proved by differentiating one of the standard recurrence relations satisfied by the ordinary Laguerre polynomials, but with n replaced by n + m. This standard equality reads xL n+m (x) = (n + m)Ln+m (x) − (n + m)Ln−1+m (x). We convert this into an equation for the associated polynomials, dm Ln+m (x), dx m by differentiating it m times with respect to x and multiplying through by (−1)m . The result is m Lm n (x) = (−1)

m m m x(Lm n ) + mLn = (n + m)Ln − (n + m)Ln−1 ,

133

Special functions

which immediately simplifies to give the second recurrence relation satisfied by the associated Laguerre polynomials. 9.9 By initially writing y(x) as x 1/2 f (x) and then making subsequent changes of variable, reduce Stokes’ equation, d 2y + λxy = 0, dx 2 to Bessel’s√ equation. Hence show that a solution that is finite at x = 0 is a multiple of x 1/2 J1/3 ( 23 λx 3 ).

With y(x) = x 1/2 f (x), f + x 1/2 f 2x 1/2 and the equation becomes y =



and

y = −

f f + + x 1/2 f 4x 3/2 x 1/2

f f + + x 1/2 f + λx 3/2 f = 0, 4x 3/2 x 1/2 x 2 f + xf + (λx 3 − 14 )f = 0.

Now, guided by the known form of Bessel’s equation, change the independent variable to u = x 3/2 with f (x) = g(u) and 3 du = x 1/2 dx 2 This gives



3 d d = u1/3 . dx 2 du

  3 1/3 dg 2/3 3 1/3 dg u u u +u u + λu2 − 2 2 du 2 du    3 dg 3 5/3 3 1/3 d 2 g 1 −2/3 dg u u + u + λu2 − + u 2 2 du2 2 du 2 du  9 2 d 2 g 9 dg u + λu2 − + u 4 du2 4 du  2 4 2 dg 2d g u + λu − +u du2 du 9 4/3 3 1/3

d du



 1 g 4  1 g 4  1 g 4  1 g 9

= 0, = 0, = 0, = 0.

This is close to Bessel’s equation but still needs a scaling of the variables. So, set μu = v and g(u) = h(v), obtaining   v dh 1 v2 2 d 2h 2 μ + μ + v − h = 0. μ2 dv 2 μ dv 9 This is Bessel’s equation and has a general solution ⇒ ⇒

h(v) = c1 J1/3 (v) + c2 J−1/3 (v),  √   √  g(u) = c1 J1/3 2 3 λ u + c2 J−1/3 2 3 λ u ,  √   √  f (x) = c1 J1/3 2 3 λ x 3/2 + c2 J−1/3 2 3 λ x 3/2 .

2 3

√ λu ≡

134

Special functions

For a solution that is finite at x = 0, only the Bessel function with a positive subscript can be accepted. Therefore the required solution is √

y(x) = c1 x 1/2 J1/3 ( 2 3 λ x 3/2 ).

9.11 The complex function z! is defined by  ∞ uz e−u du z! =

for Re z > −1.

0

For Re z ≤ −1 it is defined by z! =

(z + n)! , (z + n)(z + n − 1) · · · (z + 1)

where n is any (positive) integer > −Re z. Being the ratio of two polynomials, z! is analytic everywhere in the finite complex plane except at the poles that occur when z is a negative integer. (a) Show that the definition of z! for Re z ≤ −1 is independent of the value of n chosen. (b) Prove that the residue of z! at the pole z = −m, where m is an integer > 0, is (−1)m−1 /(m − 1)!.

(a) Let m and n be two choices of integer with m > n > −Re z. Denote the corresponding definitions of z! by (z!)m and (z!)n and consider the ratio of these two functions: (z + m)! (z + n)(z + n − 1) · · · (z + 1) (z!)m = (z!)n (z + m)(z + m − 1) · · · (z + 1) (z + n)! (z + m)! = (z + m)(z + m − 1) · · · (z + n + 1) × (z + n)! (z + m)! = 1. = (z + m)! Thus the two functions are identical for all z, i.e the definition of z! is independent of the choice of n, provided that n > −Re z. (b) From the given definition of z! it is clear that its pole at z = −m is a simple one. The residue R at the pole is therefore given by R = lim (z + m)z! z→−m

(z + m) (z + n)! (integer n is chosen > m) z→−m (z + n)(z + n − 1) · · · (z + 1) (z + n)! = lim z→−m (z + n)(z + n − 1) · · · (z + m + 1)(z + m − 1) · · · (z + 1) (−m + n)! = (−m + n) · · · (−m + m + 1)(−m + m − 1) · · · (−m + 1) 1 = [−1] [−2] · · · [−(m − 1)] 1 = (−1)m−1 , (m − 1)! = lim

as stated in the question.

135

Special functions

9.13 The integral  I=



−∞

e−k dk, k2 + a2 2

(∗)

in which a > 0, occurs in some statistical mechanics problems. By first considering the integral  ∞ J = eiu(k+ia) du 0

and a suitable variation of it, show that I = (π/a) exp(a 2 ) erfc(a), where erfc(x) is the complementary error function.

The fact that a > 0 will ensure that the improper integral J is well defined. It is  iu(k+ia) ∞  ∞ e i iu(k+ia) e du = = . J = i(k + ia) k + ia 0 0 We note that this result contains one of the factors that would appear as a denominator in one term of a partial fraction expansion of the integrand in (∗). Another term would contain a factor (k − ia)−1 , and this can be generated by  −iu(k−ia) ∞  ∞ e −i −iu(k−ia) . J = e du = = −i(k − ia) 0 k − ia 0 Now, actually expressing the integrand in partial fractions, using the integral expressions J and J for the factors, and then reversing the order of integration gives   ∞  −k2 2 ie−k ie 1 − dk I = 2a −∞ k + ia k − ia  ∞  ∞  ∞  ∞ 1 1 2 2 = e−k dk eiu(k+ia) du + e−k dk e−iu(k−ia) du, 2a −∞ 2a −∞ 0 0  ∞  ∞  ∞  ∞ 2 −k 2 +iuk−ua du e dk + du e−k −iuk−ua dk ⇒ 2aI = 0 −∞ −∞ 0 ∞ ∞ 2 2 du e−(k−iu/2) −u /4−ua dk = 0 −∞  ∞  ∞ 2 2 du e−(k+iu/2) −u /4−ua dk + 0  ∞ −∞ √ 2 e−u /4−ua du, =2 π 0

using the standard Gaussian result. We now complete the square in the exponent and set 2v = u + 2, obtaining  ∞ √ 2 2 e−(u+2a) /4+a du, 2aI = 2 π 0 ∞ √ 2 2 e−v ea 2dv. =2 π a

136

Special functions

From this it follows that √ I=

√ π 2 π a2 π 2e erfc(a) = ea erfc(a), a 2 a

as stated in the question. 9.15 Prove two of the properties of the incomplete gamma function P (a, x 2 ) as follows. (a) By considering its form for a suitable value of a, show that the error function can be expressed as a particular case of the incomplete gamma function. (b) The Fresnel integrals, of importance in the study of the diffraction of light, are given by  x  x π  π  cos sin C(x) = t 2 dt, t 2 dt. S(x) = 2 2 0 0 Show that they can be expressed in terms of the error function by  √ π (1 − i)x , C(x) + iS(x) = A erf 2 where A is a (complex) constant, which you should determine. Hence express C(x) + iS(x) in terms of the incomplete gamma function.

(a) From the definition of the incomplete gamma function, we have P (a, x 2 ) =

1 (a)



x2

e−t t a−1 dt.

0

√ Guided by the x 2 in the upper limit, we now change the integration variable to y = + t, with 2y dy = dt, and obtain P (a, x 2 ) =

1 (a)



x

e−y y 2(a−1) 2y dy. 2

0

To make the RHS into an error function we need to remove the y-term; to do this we √ choose a such that 2(a − 1) + 1 = 0, i.e. a = 12 . With this choice, (a) = π and P

1

,x 2

2



2 =√ π



x

e−y dy, 2

0

i.e. a correctly normalized error function. (b) Consider the given expression:  √  √π(1−i)x/2 π 2A 2 (1 − i)x = √ e−u du. z = A erf 2 π 0

137

Special functions

√ Changing the variable of integration to s, given by u = 12 π (1 − i)s, and recalling that (1 − i)2 = −2i, we obtain √  x 2A π 2 z= √ (1 − i) ds e−s π(−2i)/4 2 π 0  x 2 eiπs /2 ds = A(1 − i) 0

 = A(1 − i) 0

x

 2   2 πs πs + i sin ds cos 2 2

= A(1 − i) [C(x) + iS(x)]. For the correct normalization we need A(1 − i) = 1, implying that A = (1 + i)/2. Now, from part (a), the error function can be expressed in terms of the incomplete gamma function P (a, x) by   erf(x) = P 12 , x 2 . √ Here the argument of the error function is 12 π (1 − i)x, whose square is − 12 πix 2 , and so   1+i 1 iπ 2 C(x) + iS(x) = P ,− x . 2 2 2

10

Partial differential equations

10.1 Determine whether the following can be written as functions of p = x 2 + 2y only, and hence whether they are solutions of ∂u ∂u =x . ∂x ∂y (a) x 2 (x 2 − 4) + 4y(x 2 − 2) + 4(y 2 − 1); (b) x 4 + 2x 2 y + y 2 ; (c) [x 4 + 4x 2 y + 4y 2 + 4]/[2x 4 + x 2 (8y + 1) + 8y 2 + 2y].

As a first step, we verify that any function of p = x 2 + 2y will satisfy the given equation. Using the chain rule, we have



∂u ∂p ∂u ∂p =x , ∂p ∂x ∂p ∂y ∂u ∂u 2x = x 2. ∂p ∂p

This is satisfied for any function u(p), thus completing the verification. To test the given functions we substitute for y = 12 (p − x 2 ) or for x 2 = p − 2y in each of the f (x, y) and then examine whether the resulting forms are independent of x or y, respectively. (a) f (x, y) = x 2 (x 2 − 4) + 4y(x 2 − 2) + 4(y 2 − 1) = x 2 (x 2 − 4) + 2(p − x 2 )(x 2 − 2) + p2 − 2p x 2 + x 4 − 4 = x 4 (1 − 2 + 1) + x 2 (−4 + 2p + 4 − 2p) − 4p + p2 − 4 = p 2 − 4p − 4 = g(p). This is a function of p only, and therefore the original f (x, y) is a solution of the PDE. Though not necessary for answering the question, we will repeat the verification, but this time by substituting for x rather than for y: f (x, y) = x 2 (x 2 − 4) + 4y(x 2 − 2) + 4(y 2 − 1) = (p − 2y)(p − 2y − 4) + 4y(p − 2y − 2) + 4(y 2 − 1) = p 2 − 4py + 4y 2 − 4p + 8y + 4yp − 8y 2 − 8y + 4y 2 − 4 = p 2 − 4p − 4 = g(p); 138

139

Partial differential equations

i.e. it is the same as before, as it must be, and again this shows that f (x, y) is a solution of the PDE. (b) f (x, y) = x 4 + 2x 2 y + y 2 = (p − 2y)2 + 2y(p − 2y) + y 2 = p 2 − 4p y + 4y 2 + 2p y − 4y 2 + y 2 = (p − y)2 = g(p). As this is a function of both p and y, it is not a solution of the PDE. x 4 + 4x 2 y + 4y 2 + 4 2x 4 + x 2 (8y + 1) + 8y 2 + 2y p 2 − 4p y + 4y 2 + 4yp − 8y 2 + 4y 2 + 4 = 2 2p − 8p y + 8y 2 + 8yp + p − 16y 2 − 2y + 8y 2 + 2y p2 + 4 = g(p). = 2p 2 + p

(c) f (x, y) =

This is a function of p only and therefore f (x, y) is a solution of the PDE. 10.3 Solve the following partial differential equations for u(x, y) with the boundary conditions given: ∂u + xy = u, ∂x ∂u (b) 1 + x = xu, ∂y

(a) x

u = 2y on the line x = 1; u(x, 0) = x.

(a) This can be solved as an ODE for u as a function of x, though the “constant of integration” will be a function of y. In standard form, the equation reads ∂u u − = −y. ∂x x By inspection (or formal calculation) the IF for this is x −1 and the equation can be rearranged as y ∂ u = − , ∂x x x u = −y ln x + f (y), ⇒ x u = 2y on x = 1 ⇒ f (y) = 2y, and so u(x, y) = xy(2 − ln x). (b) This equation can be written in standard form, with u as a function of y: ∂u 1 −u=− , ∂y x

140

Partial differential equations

for which the IF is clearly e−y , leading to ∂  −y  e−y , e u = − ∂y x e−y + f (x), ⇒ e−y u = x u(x, 0) = x ⇒ f (x) = x −

1 . x

Substituting this result, and multiplying through by ey , gives u(x, y) as   1 1 y u(x, y) = + x − e . x x 10.5 Find solutions of 1 ∂u 1 ∂u + =0 x ∂x y ∂y for which (a) u(0, y) = y and (b) u(1, 1) = 1.

As usual, we find p (x, y) from dy dx = −1 −1 x y



x 2 − y 2 = p.

(a) On x = 0, p = −y 2 and u(0, y) = y = (−p )1/2



u(x, y) = [−(x 2 − y 2 )]1/2 = (y 2 − x 2 )1/2 .

(b) At (1, 1), p = 0 and u(1, 1) = 1



u(x, y) = 1 + g(x 2 − y 2 ),

where g is any function that has g(0) = 0. We note that in part (a) the solution is uniquely determined because the boundary values are given along a line, whereas in part (b), where the value is fixed at only an isolated point, the solution is indeterminate to the extent of a loosely determined function. This is the normal situation, though it is modified if the boundary line in (a) happens to be one along which p has a constant value. 10.7 Solve sin x

∂u ∂u + cos x = cos x ∂x ∂y

(∗)

subject to (a) u(π/2, y) = 0 and (b) u(π/2, y) = y(y + 1).

As usual, the CF is found from dy dx = sin x cos x



y − ln sin x = p.

141

Partial differential equations

Since the RHS of (∗) is a factor in one of the terms on the LHS, a trivial PI is any function of y only whose derivative (with respect to y) is unity, of which the simplest is u(x, y) = y. The general solution is therefore u(x, y) = f (y − ln sin x) + y. The actual form of the arbitrary function f (p) is determined by the form that u(x, y) takes on the boundary, here the line x = π/2. (a) With u(π/2, y) = 0: 0 = f (y − 0) + y ⇒



f (p ) = −p

u(x, y) = ln sin x − y + y = ln sin x.

(b) With u(π/2, y) = y(y + 1): y(y + 1) = f (y − 0) + y ⇒



f (p ) = p 2

u(x, y) = (y − ln sin x)2 + y.

10.9 If u(x, y) satisfies ∂ 2u ∂ 2u ∂ 2u −3 +2 2 =0 2 ∂x ∂x∂y ∂y and u = −x 2 and ∂u/∂y = 0 for y = 0 and all x, find the value of u(0, 1).

If we are to find solutions to this homogeneous second-order PDE of the form u(x, y) = f (x + λy), then λ must satisfy 1 − 3λ + 2λ2 = 0



λ = 12 , 1.

Thus u(x, y) = g(x + 12 y) + f (x + y) ≡ g(p1 ) + f (p2 ). On y = 0, p 1 = p 2 = x and −x 2 = u(x, 0) = g(x) + f (x), ∂u (x, 0) = 12 g (x) + f (x). 0= ∂y From (∗), − 2x = g (x) + f (x). Subtracting, Integrating, Hence,

(∗)

2x = − 12 g (x). g(x) = −2x 2 + k ⇒ f (x) = x 2 − k, 2  u(x, y) = −2 x + 12 y + k + (x + y)2 − k = −x 2 + 12 y 2 .

At the particular point (0, 1) we have u(0, 1) = −02 + 12 (1)2 = 12 .

from (∗).

142

Partial differential equations

10.11 In those cases in which it is possible to do so, evaluate u(2, 2), where u(x, y) is the solution of 2y

∂u ∂u −x = xy(2y 2 − x 2 ) ∂x ∂y

that satisfies the (separate) boundary conditions given below. (a) u(x, √ 1) = x 2 . (b) u(1, √ 10) = 5. (c) u( 10, 1) = 5.

To find the CF, u(x, y) = f (p ), we set dx dy =− 2y x



x 2 + 2y 2 = p.

The point (2, 2) corresponds to p = 22 + 2(22 ) = 12. For a PI we try u(x, y) = Ax n y m : 2Anx n−1 y m+1 − Amx n+1 y m−1 = 2xy 3 − x 3 y, which has a solution, n = m = 2 with A = 12 . Thus the general solution is u(x, y) = f (x 2 + 2y 2 ) + 12 x 2 y 2 . (a) We must find the function f that makes u(x, 1) = x 2 . This requires f to satisfy x 2 = u(x, 1) = f (x 2 + 2) + 12 x 2 ⇒ ⇒

f (p) = 12 (p − 2) u(x, y) = 12 (x 2 + 2y 2 − 2) + 12 x 2 y 2 = 12 (x 2 + x 2 y 2 + 2y 2 − 2).

From which it follows that u(2, 2) = 12 (4 + 16 + 8 − 2) = 13. √ √ (b) With u(1, 10) = 5: At the point (1, 10) the value of p is 1 + 2(10) = 21. As the “boundary” consists of just this one point, it is only at the points that have p = 21 that the value of u(x, y) can be known. Since for the point (2, 2) the value of p is 12, the value of u(2, 2) cannot√be determined. √ (c) With u( 10, 1) = 5: At the point ( 10, 1) the value of p is 10 + 2(1) = 12. Since for (2, 2) it is also 12, the value of u(2, 2) can be determined and is given by f (12) + 1 (4)(4) = 5 + 8 = 13. 2

10.13 Find the most general solution of

∂ 2u ∂ 2u + 2 = x2y2. ∂x 2 ∂y

The complementary function for this equation is the solution to the two-dimensional Laplace equation and [either as a general known result or from substituting the trial form h(x + λy) which leads to λ2 = −1 and hence to λ = ±i] has the form f (x + iy) + g(x − iy) for arbitrary functions f and g. It therefore remains only to find a suitable PI. As f and g are not specified, there are infinitely many possibilities and which one we finish up with will depend upon the details

143

Partial differential equations

of the approach adopted. When a solution has been obtained it should be checked by substitution. As no PI is obvious by inspection, we make a change of variables with the object of obtaining one by means of an explicit integration. To do this, we use as new variables the arguments of the arbitrary functions appearing in the CF. Setting ξ = x + iy and η = x − iy, with u(x, y) = v(ξ, η), gives    ∂ ∂ ∂v ∂v + + ∂ξ ∂η ∂ξ ∂η        ∂ ∂v ∂v ξ +η 2 ξ −η 2 ∂ −i i −i = , + i ∂ξ ∂η ∂ξ ∂η 2 2i ∂ 2v ∂ 2v ∂ 2v 1 + (1 − 1) 2 = − (ξ 2 − η2 )2 , (1 − 1) 2 + (2 + 2) ∂ξ ∂ξ ∂η ∂η 16 2 1 ∂ v = − (ξ 2 − η2 )2 . ∂ξ ∂η 64 When we integrate this we can set all constants of integration and all arbitrary functions equal to zero as any solution will suffice: 1 ∂ 2v = − (ξ 4 − 2ξ 2 η2 + η4 ), ∂ξ ∂η 64   ∂v 1 ξ5 2ξ 3 η2 4 =− − + ξη , ∂η 64 5 3   ξ η5 1 ξ 5 η 2ξ 3 η3 − + . v=− 64 5 9 5 Re-expressing this solution as a function of x and y (noting that ξ η = x 2 + y 2 ) gives u(x, y) = = = = = Check Applying

1 [10ξ 3 η3 − 9ξ η(ξ 4 + η4 )] (64)(45) 1 [10(x 2 + y 2 )3 − 18(x 2 + y 2 )(x 4 − 6x 2 y 2 + y 4 )] (64)(45) x2 + y2 (10x 4 + 20x 2 y 2 + 10y 4 − 18x 4 + 108x 2 y 2 − 18y 4 ) (64)(45) x2 + y2 (128x 2 y 2 − 8x 4 − 8y 4 ) (64)(45) 1 (15x 4 y 2 − x 6 + 15x 2 y 4 − y 6 ). 360

∂2 ∂2 + to the final expression yields ∂x 2 ∂y 2

1 [15(12)x 2 y 2 − 30x 4 + 30y 4 + 30x 4 + 15(12)x 2 y 2 − 30y 4 ] = x 2 y 2 , 360 as it should.

144

Partial differential equations

10.15 The non-relativistic Schr¨odinger equation, −2

h 2 ∂u ∇ u + V (r)u = i − h , 2m ∂t is similar to the diffusion equation in having different orders of derivatives in its various terms; this precludes solutions that are arbitrary functions of particular linear combinations of variables. However, since exponential functions do not change their forms under differentiation, solutions in the form of exponential functions of combinations of the variables may still be possible. Consider the Schr¨odinger equation for the case of a constant potential, i.e. for a free particle, and show that it has solutions of the form A exp(lx + my + nz + λt), where the only requirement is that −



 h 2 l + m2 + n2 = i − hλ. 2m −2

In particular, identify the equation and wavefunction obtained by taking λ as −iE/− h, and l, m and n as ipx /− h, ipy /− h and ipz /− h, respectively, where E is the energy and p the momentum of the particle; these identifications are essentially the content of the de Broglie and Einstein relationships.

For a free particle we may omit the potential term V (r) from the Schr¨odinger equation, which then reads (in Cartesian coordinates)  −2  2 ∂ u ∂ 2u ∂ 2u h ∂u = i− + + h . − 2 2 2 2m ∂x ∂y ∂z ∂t We try u(x, y, z, t) = A exp(lx + my + nz + λt), i.e. the product of four exponential functions, and obtain −

−2

h 2 hλu. (l + m2 + n2 )u = i − 2m

This equation is clearly satisfied provided −

−2

h 2 (l + m2 + n2 ) = i − hλ. 2m

h, and l, m and n as ipx /− h, ipy /− h and ipz /− h, respectively, where E is the With λ as −iE/− energy and p is the momentum of the particle, we have   −2 py2 pz2 px2 h − 2 − 2 − 2 = E, − − − − 2m h h h which can be written more compactly as E = p 2 /2m, the classical non-relativistic relationship between the (kinetic) energy and momentum of a free particle. The wavefunction obtained is   i u(r, t) = A exp − (px x + py y + pz z − Et) h   i = A exp − (p · r − Et) , h

145

Partial differential equations

i.e. a classical plane wave of wave number k = p/− h and angular frequency ω = E/− h traveling in the direction p/p. 10.17 An incompressible fluid of density ρ and negligible viscosity flows with velocity v along a thin, straight, perfectly light and flexible tube, of cross-section A which is held under tension T . Assume that small transverse displacements u of the tube are governed by   2 ∂ u ∂ 2u ∂ 2u T 2 + v + 2v − = 0. 2 ∂t ∂x∂t ρA ∂x 2 (a) Show that the general solution consists of a superposition of two waveforms traveling with different speeds. (b) The tube initially has a small transverse displacement u = a cos kx and is suddenly released from rest. Find its subsequent motion.

(a) This is a second-order equation and will (in general) have two solutions of the form u(x, t) = f (x + λt), where both λ satisfy ,   T T 2 2 λ + 2vλ + v − = 0 ⇒ λ = −v ± v 2 − v 2 + ≡ −v ± α, ρA ρA and gives (minus) the speed of the corresponding profile. Thus the general displacement consists of a superposition of waveforms traveling with speeds v ∓ α. ˙ 0) = 0, where the dot denotes differentiation with (b) Now u(x, 0) = a cos kx and u(x, respect to time t. Let the general solution be given by u(x, t) = f [x − (v + α)t] + g[x − (v − α)t], with and

a cos kx = f (x) + g(x) 0 = −(v + α)f (x) − (v − α)g (x).

We differentiate the first of these with respect to x and then eliminate the function f (x): −ka sin kx = f (x) + g (x), −ka(v + α) sin kx = (v + α − v + α)g (x), ka(v + α) sin kx, g (x) = − 2α v+α ⇒ g(x) = a cos kx + c, 2α α−v ⇒ f (x) = a cos kx − c. 2α Now that the forms of the initially arbitrary functions f (x) and g(x) have been determined, it follows that, for a general time t, α+v α−v a cos[kx − k(v + α)t] + a cos[kx − k(v − α)t] u(x, t) = 2α 2α a va = 2 cos(kx − kvt) cos kαt + 2 sin(kx − kvt) sin(−kαt) 2 2α va sin[k(x − vt)] sin kαt. = a cos[k(x − vt)] cos kαt − α

146

Partial differential equations

10.19 In an electrical cable of resistance R and capacitance C, each per unit length, voltage signals obey the equation ∂ 2 V /∂x 2 = RC∂V /∂t. This (diffusion-type) equation has solutions of the form  ζ 2 x(RC)1/2 f (ζ ) = √ exp(−ν 2 ) dν, where ζ = . 2t 1/2 π 0 It also has solutions of the form V = Ax + D. (a) Find a combination of these that represents the situation after a steady voltage V0 is applied at x = 0 at time t = 0. (b) Obtain a solution describing the propagation of the voltage signal resulting from the application of the signal V = V0 for 0 < t < T , V = 0 otherwise, to the end x = 0 of an infinite cable. (c) Show that for t  T the maximum signal occurs at a value of x proportional to t 1/2 and has a magnitude proportional to t −1 .

(a) Consider the given function  ζ 2 x(RC)1/2 f (ζ ) = √ exp(−ν 2 ) dν, where ζ = . 2t 1/2 π 0 The requirements to be satisfied by the correct combination of this function and V (x, t) = Ax + D are (i) that, at t = 0, V is zero for all x, except x = 0 where it is V0 , and (ii) that, as t → ∞, V is V0 for all x. (i) At t = 0, ζ = ∞ and f (ζ ) = 1 for all x = 0. (ii) As t → ∞, ζ → 0 and f (ζ ) → 0 for all finite x. The required combination is therefore D = V0 and −V0 f (ζ ), i.e. ⎤ ⎡  1 x(CR/t)1/2 2 2 exp(−ν 2 ) dν ⎦ . V (x, t) = V0 ⎣1 − √ π 0 (b) The equation is linear and so we may superpose solutions. The response to the input V = V0 for 0 < t < T can be considered as that to V0 applied at t = 0 and continued, together with −V0 applied at t = T and continued. The solution is therefore the difference between two solutions of the form found in part (a):  1 1/2   2V0 2 x[CR/(t−T )] exp −ν 2 dν. V (x, t) = √ π 21 x(CR/t)1/2 (c) To find the maximum signal we set ∂V /∂x equal to zero. Remembering that we are differentiating with respect to the limits of an integral (whose integrand does not contain x explicitly), we obtain         2 1 CR 1/2 1 CR 1/2 x 2 CR x CR − = 0. exp − exp − 2 t −T 4(t − T ) 2 t 4t This requires



t −T t

1/2

 x 2 CR x 2 CR + = exp − 4(t − T ) 4t  2  x CR(−t + t − T ) = exp . 4t(t − T ) 

147

Partial differential equations

For t  T , we expand both sides: 1−

1T T x 2 CR + ··· = 1 − + · · ·, 2 t 4t 2 '   1 2t CR 1/2 2t 1 2 ⇒ ν= ⇒ x ≈ =√ . CR 2 CR t 2

The corresponding value of V is approximately equal to the value of the integrand, evaluated at this value of ν, multiplied by the difference between the two limits of the integral. Thus √   1 2V0 1 2 x CR Vmax ≈ √ exp(−ν ) − 2 (t − T )1/2 t 1/2 π √ x CR 1 T 2V0 ≈ √ e−1/2 2 2 t 3/2 π V0 T e−1/2 . = √ 2π t In summary, for t  T the maximum signal occurs at a value of x proportional to t 1/2 and has a magnitude proportional to t −1 . 10.21 Consider each of the following situations in a qualitative way and determine the equation type, the nature of the boundary curve and the type of boundary conditions involved: (a) (b) (c) (d)

a conducting bar given an initial temperature distribution and then thermally isolated; two long conducting concentric cylinders, on each of which the voltage distribution is specified; two long conducting concentric cylinders, on each of which the charge distribution is specified; a semi-infinite string, the end of which is made to move in a prescribed way.

We use the notation A

∂ 2u ∂u ∂ 2u ∂u ∂ 2u +C 2 +D +E + F u = R(x, y) +B 2 ∂x ∂x∂y ∂y ∂x ∂y

to express the most general type of PDE, and the following table Equation type

Boundary

Conditions

hyperbolic parabolic elliptic

open open closed

Cauchy Dirichlet or Neumann Dirichlet or Neumann

to determine the appropriate boundary type and hence conditions. ∂T ∂ 2T (a) The diffusion equation κ 2 = has A = κ, B = 0 and C = 0; thus B 2 = 4AC ∂x ∂t and the equation is parabolic. This needs an open boundary. In the present case, the initial heat distribution (at the t = 0 boundary) is a Dirichlet condition and the insulation (no temperature gradient at the external surfaces) is a Neumann condition.

148

Partial differential equations

(b) The governing equation in two-dimensional Cartesians (not the natural choice for this situation, but this does not matter for the present purpose) is the Laplace equation, ∂ 2φ ∂ 2φ + = 0, which has A = 1, B = 0 and C = 1 and therefore B 2 < 4AC. The ∂x 2 ∂y 2 equation is therefore elliptic and requires a closed boundary. Since φ is specified on the cylinders, the boundary conditions are Dirichlet in this particular situation. (c) This is the same as part (b) except that the specified charge distribution σ determines ∂φ/∂n, through ∂φ/∂n = σ/ 0 , and imposes Neumann boundary conditions. 1 ∂ 2u ∂ 2u (d) For the wave equation 2 − 2 2 = 0, we have A = 1, B = 0 and C = −c−2 , ∂x c ∂t thus making B 2 > 4AC and the equation hyperbolic. We thus require an open boundary and Cauchy conditions, with the displacement of the end of the string having to be specified at all times – this is equivalent to the displacement and the velocity of the end of the string being specified at all times. 10.23 The Klein–Gordon equation (which is satisfied by the quantum-mechanical wavefunction (r) of a relativistic spinless particle of non-zero mass m) is ∇ 2  − m2  = 0. Show that the solution for the scalar field (r) in any volume V bounded by a surface S is unique if either Dirichlet or Neumann boundary conditions are specified on S.

Suppose that, for a given set of boundary conditions ( = f or ∂/∂n = g on S), there are two solutions to the Klein–Gordon equation, 1 and 2 . Then consider 3 = 1 − 2 , which satisfies ∇ 2 3 = ∇ 2 1 − ∇ 2 2 = m2 1 − m2 2 = m2 3 and ∂3 = g − g = 0 on S. ∂n Now apply Green’s first theorem with the scalar functions equal to 3 and ∗3 :  S  ∗ ∂3 3 dS = [∗3 ∇ 2 3 + (∇∗3 ) · (∇3 )] dV , ∂n V ⇒ 0 = (m2 |3 |2 + |∇3 |2 ) dV , either 3 = f − f = 0, or

V

whichever set of boundary conditions applies. Since both terms in the integrand on the RHS are non-negative, each must be equal to zero. In particular, |3 | = 0 implies that 3 = 0 everywhere, i.e. 1 = 2 everywhere; the solution is unique.

11

Solution methods for PDEs

11.1 Solve the following first-order partial differential equations by separating the variables: (a)

∂u ∂u −x = 0; ∂x ∂y

(b) x

∂u ∂u − 2y = 0. ∂x ∂y

In each case we write u(x, y) = X(x)Y (y), separate the variables into groups that each depend on only one variable, and then assert that each must be equal to a constant, with the several constants satisfying an arithmetic identity. (a)

∂u ∂u −x ∂x ∂y X Y − xXY Y X = =k xX Y

=

0,

=

0,



ln X = 12 kx 2 + c1 ,



X = Aekx

u(x, y)

=

Ceλ(x

∂u ∂u − 2y ∂x ∂y xX Y − 2yXY 2yY xX = =k X Y

=

0,

=

0,



ln X = k ln x + c1 ,

⇒ (b)

x

2

+2y)

2

/2

,

ln Y = ky + c2 ,

Y = Beky ,

, where k = 2λ.

ln Y = 12 k ln y + c2 , ⇒

u(x, y)

Y = By k/2 ,



X = Ax k ,

=

C(x 2 y)λ , where k = 2λ.

11.3 The wave equation describing the transverse vibrations of a stretched membrane under tension T and having a uniform surface density ρ is   2 ∂ 2u ∂ u ∂ 2u =ρ 2. + T 2 2 ∂x ∂y ∂t

149

150

Solution methods for PDEs Find a separable solution appropriate to a membrane stretched on a frame of length a and width b, showing that the natural angular frequencies of such a membrane are given by   π 2 T n2 m2 2 + 2 , ω = ρ a2 b where n and m are any positive integers.

We seek solutions u(x, y, t) that are periodic in time and have u(0, y, t) = u(a, y, t) = u(x, 0, t) = u(x, b, t) = 0. Write u(x, y, t) = X(x)Y (y)S(t) and substitute, obtaining T (X Y S + XY S) = ρXYS , which, when divided through by XYS, gives Y ρ S ω2 ρ X + = =− . X Y T S T The second equality, obtained by applying the separation of variables principle with separation constant −ω2 ρ/T , gives S(t) as a sinusoidal function of t of frequency ω, i.e. A cos(ωt) + B sin(ωt). We then have, on applying the separation of variables principle a second time, that Y ω2 ρ X = λ and = μ, where λ + μ = − . X Y T

(∗)

These equations must also have sinusoidal solutions. This is because, since u(0, y, t) = u(a, y, t) = u(x, 0, t) = u(x, b, t) = 0, each solution has to have zeros at two different values of its argument. We are thus led to X = A sin(p x) and Y = B sin(q x), where p 2 = −λ and q 2 = −μ. Further, since u(a, y, t) = u(x, b, t) = 0, we must have p = nπ/a and q = mπ/b, where n and m are integers. Putting these values back into (∗) gives  2  ω2 ρ ω2 ρ m2 2 2 2 n = + −p − q = − ⇒ π . T a2 b2 T Hence the quoted result. 11.5 Denoting the three terms of ∇ 2 in spherical polars by ∇r2 , ∇θ2 , ∇φ2 in an obvious way, evaluate ∇r2 u, etc. for the two functions given below and verify that, in each case, although the individual terms are not necessarily zero their sum ∇ 2 u is zero. Identify the corresponding values of  and m.   B 3 cos2 θ − 1 (a) u(r, θ, φ) = Ar 2 + 3 . r 2  B (b) u(r, θ, φ) = Ar + 2 sin θ exp iφ. r

151

Solution methods for PDEs

In both cases we write u(r, θ, φ) as R(r)(θ)(φ) with

∇r2

1 ∂ = 2 r ∂r

    1 1 ∂ ∂ ∂2 2 ∂ 2 . r , ∇θ = 2 sin θ , ∇φ2 = 2 2 ∂r r sin θ ∂θ ∂θ r sin θ ∂φ 2



B (a) u(r, θ, φ) = Ar + 3 r



2

3 cos2 θ − 1 . 2

    3B 6B 6u 3 2Ar − 2  = 6A + 5  = 2 , r r r   R 1 ∂ R −6 sin θ cos2 θ + 3 sin3 θ 2 2 ∇θ u = 2 (−3 sin θ cos θ) = 2 r sin θ ∂θ r sin θ 6u R = 2 (−9 cos2 θ + 3) = − 2 , r r ∇r2 u

1 ∂ = 2 r ∂r

∇φ2 u = 0. Thus, although ∇r2 u and ∇θ2 u are not individually zero, their sum is. From ∇r2 u = ( + 1)u = 6u, we deduce that  = 2 (or −3) and from ∇φ2 u = 0 that m = 0.   B (b) u(r, θ, φ) = Ar + 2 sin θ eiφ . r 





 2A 2B 2u  = + 4  = 2 , r r r   R 1 ∂ R − sin2 θ + cos2 θ 2 ∇θ u = 2 (sin θ cos θ) = 2 r sin θ ∂θ r sin θ cos2 θ u u , =− 2 + r sin2 θ r 2

∇r2 u

1 ∂ = 2 r ∂r

∇φ2 u =

2B Ar − r 2

R ∂ 2 iφ u (e ) = − 2 2 . r 2 sin2 θ ∂φ 2 r sin θ

Hence, ∇ 2u =

u 2u u cos2 θ u u − + − 2 2 = 2 2 2 2 2 r r sin θ r r sin θ r

 1+

cos2 θ − 1 sin2 θ

 = 0.

Here each individual term is non-zero, but their sum is zero. Further, ( + 1) = 2 and so  = 1 (or −2), and from ∇φ2 u = −u/(r 2 sin θ) it follows that m2 = 1. In fact, from the normal definition of spherical harmonics, m = +1.

152

Solution methods for PDEs

11.7 If the stream function ψ(r, θ ) for the flow of a very viscous fluid past a sphere is written as ψ(r, θ ) = f (r) sin2 θ , then f (r) satisfies the equation 4f 8f 8f + − 4 = 0. 2 3 r r r At the surface of the sphere r = a the velocity field u = 0, whilst far from the sphere ψ  (U r 2 sin2 θ )/2. Show that f (r) can be expressed as a superposition of powers of r, and determine which powers give acceptable solutions. Hence show that   a3 U 2 2r − 3ar + sin2 θ. ψ(r, θ ) = 4 r f (4) −

For solutions of f (4) −

4f 8f 8f + − 4 =0 r2 r3 r

that are powers of r, i.e. have the form Ar n , n must satisfy the quartic equation n(n − 1)(n − 2)(n − 3) − 4n(n − 1) + 8n − 8 = 0, (n − 1)[n(n − 2)(n − 3) − 4n + 8] = 0, (n − 1)(n − 2)[n(n − 3) − 4] = 0, (n − 1)(n − 2)(n − 4)(n + 1) = 0. Thus the possible powers are 1, 2, 4 and −1. Since ψ → 12 U r 2 sin2 θ as r → ∞, the solution can contain no higher (positive) power of r than the second. Thus there is no n = 4 term and the solution has the form   2 B Ur + Ar + sin2 θ. ψ(r, θ) = 2 r On the surface of the sphere r = a both velocity components, ur and uθ , are zero. These components are given in terms of the stream functions, as shown below; note that ur is found by differentiating with respect to θ and uθ by differentiating with respect to r. U a2 B + Aa + = 0, 2 a

ur = 0



1 ∂ψ =0 2 a sin θ ∂θ

uθ = 0



−1 ∂ψ =0 a sin θ ∂r



A = − 34 U a and B = 14 U a 3 .

⇒ ⇒

Ua + A −

The full solution is thus U ψ(r, θ) = 4



a3 2r − 3ar + r 2

 sin2 θ.

B = 0, a2

153

Solution methods for PDEs

11.9 A circular disc of radius a is heated in such a way that its perimeter ρ = a has a steady temperature distribution A + B cos2 φ, where ρ and φ are plane polar coordinates and A and B are constants. Find the temperature T (ρ, φ) everywhere in the region ρ < a.

This is a steady state problem, for which the (heat) diffusion equation becomes the Laplace equation. The most general single-valued solution to the Laplace equation in plane polar coordinates is given by T (ρ, φ) = C ln ρ + D +

∞ 

(An cos nφ + Bn sin nφ)(Cn ρ n + Dn ρ −n ).

n=1

The region ρ < a contains the point ρ = 0; since ln ρ and all ρ −n become infinite at that point, C = Dn = 0 for all n. On ρ = a T (a, φ) = A + B cos2 φ = A + 12 B(cos 2φ + 1). Equating the coefficients of cos nφ, including n = 0, gives A + 12 B = D, A2 C2 a 2 = 12 B and An Cn a n = 0 for all n = 2; further, all Bn = 0. The solution everywhere (not just on the perimeter) is therefore B Bρ 2 + 2 cos 2φ. 2 2a It should be noted that “equating coefficients” to determine unknown constants is justified by the fact that the sinusoidal functions in the sum are mutually orthogonal over the range 0 ≤ φ < 2π. T (ρ, φ) = A +

11.11 The free transverse vibrations of a thick rod satisfy the equation ∂ 4u ∂ 2u + 2 = 0. ∂x 4 ∂t Obtain a solution in separated-variable form and, for a rod clamped at one end, x = 0, and free at the other, x = L, show that the angular frequency of vibration ω satisfies  1/2   1/2  ω L ω L cosh = − sec . a a a4

[At a clamped end both u and ∂u/∂x vanish, whilst at a free end, where there is no bending moment, ∂ 2 u/∂x 2 and ∂ 3 u/∂x 3 are both zero.]

The general solution is written as the product u(x, t) = X(x)T (t), which, on substitution, produces the separated equation T X(4) =− = ω2 . X T Here the separation constant has been chosen so as to give oscillatory behavior (in the time variable). The spatial equation then becomes a4

X(4) − μ4 X = 0, where μ = ω1/2 /a.

154

Solution methods for PDEs

The required auxiliary equation is λ4 − μ4 = 0, leading to the general solution X(x) = A sin μx + B cos μx + C sinh μx + D cosh μx. The constants A, B, C and D are to be determined by requiring X(0) = X (0) = 0 and X (L) = X (L) = 0. At the clamped end, X(0) = 0



D = −B,



=

μ(A cos μx − B sin μx + C cosh μx − B sinh μx),

X (0) = 0



C = −A.

X

At the free end, X = μ2 (−A sin μx − B cos μx − A sinh μx − B cosh μx), X = μ3 (−A cos μx + B sin μx − A cosh μx − B sinh μx), X (L) = 0

X (L) = 0



A(sin μL + sinh μL) + B(cos μL + cosh μL) = 0,



A(− cos μL − cosh μL) + B(sin μL − sinh μL) = 0.

Cross-multiplying then gives − sin2 μL + sinh2 μL = cos2 μL + 2 cos μL cosh μL + cosh2 μL, 0 = 1 + 2 cos μL cosh μL + 1, −1 = cos μL cosh μL,   1/2  ω L ω1/2 L = − sec . cosh a a 

Because sinusoidal and hyperbolic functions can all be written in terms of exponential functions, this problem could also be approached by assuming solutions that are (exponential) functions of linear combinations of x and t (as in Chapter 10). However, in practice, eliminating the t-dependent terms leads to involved algebra. 11.13 A string of length L, fixed at its two ends, is plucked at its mid-point by an amount A and then released. Prove that the subsequent displacement is given by     ∞  8A (2n + 1)πct (2n + 1)πx cos , sin u(x, t) = π 2 (2n + 1)2 L L n=0 where, in the usual notation, c2 = T /ρ. Find the total kinetic energy of the string when it passes through its unplucked position, by calculating it in each mode (each n) and summing, using the result ∞  0

1 π2 . = (2n + 1)2 8

Confirm that the total energy is equal to the work done in plucking the string initially.

155

Solution methods for PDEs

We start with the wave equation: 1 ∂ 2u ∂ 2u − =0 ∂x 2 c2 ∂t 2 and assume a separated-variable solution u(x, t) = X(x)S(t). This leads to X 1 S = 2 = −k 2 . X c S The solution to the spatial equation is given by X(x) = B cos kx + C sin kx. Taking the string as anchored at x = 0 and x = L, we must have B = 0 and k constrained by sin kL = 0 ⇒ k = nπ/L with n an integer. The solution to the corresponding temporal equation is S(t) = D cos kct + E sin kct. ˙ Since there is no initial motion, i.e. S(0) = 0, it follows that E = 0. For any particular value of k, the constants C and D can be amalgamated. The general solution is given by a superposition of the allowed functions, i.e.

u(x, t) =

∞ 

Cn sin

n=1

nπx nπct cos . L L

We now have to determine the Cn by making u(x, 0) match the given initial configuration, which is ⎧ 2Ax ⎪ ⎨ L u(x, 0) = ⎪ ⎩ 2A(L − x) L

for 0 ≤ x ≤ L < x ≤ L. 2

L , 2

This is now a Fourier series calculation yielding Cn L = 2



L/2

nπx 2Ax sin dx + L L 0 2A 2A J1 + 2AJ2 − J3 , = L L



L

L/2

nπx 2A(L − x) sin dx L L

156

Solution methods for PDEs

with    L/2 nπx L/2 nπx L xL J1 = − cos cos dx + nπ L 0 nπ L 0 L2 nπ L2 nπ =− cos + 2 2 sin , 2πn 2 nπ 2  L L " nπx #L nπx dx = − cos J2 = sin L nπ L L/2 L/2 L " nπ # =− (−1)n − cos , nπ 2    L nπx L nπx L xL cos cos dx + J3 = − nπ L L/2 L L/2 nπ =

L2 L2 nπ nπ L2 cos − (−1)n − 2 2 sin . 2πn 2 nπ nπ 2

Thus nπ L2 2L2 2L2 nπ cos + (−1)n + 2 2 sin 2πn 2 nπ nπ 2 2 2L nπ , = −LJ2 + 2 2 sin nπ 2

J1 − J3 = −

and so it follows that Cn L 2A 2L nπ = (J1 − J3 + LJ2 ) = 2A 2 2 sin . 2 L nπ 2 This is zero if n is even and Cn = 8A(−1)(n−1)/2 /(n2 π 2 ) if n is odd. Write n = 2m + 1, 8A(−1)m . (2m + 1)2 π 2 The final solution (in which m is replaced by n, to match the question) is thus

m = 0, 1, 2, . . ., with C2m+1 =

    ∞  (2n + 1)πx (2n + 1)πct 8A(−1)n sin u(x, t) = cos . π 2 (2n + 1)2 L L n=0 The velocity profile derived from this is given by ˙ t) = u(x,

  ∞  −(2n + 1)πc 8A(−1)n π 2 (2n + 1)2 L n=0     (2n + 1)πct (2n + 1)πx sin , × sin L L

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Solution methods for PDEs

giving the energy in the (2n + 1)th mode (evaluated when the time-dependent sine function is maximal) as  L 1 ρ u˙ 2n dx E2n+1 = 2 0



L

= 0

=

(8A)2 c2 ρ (2n + 1)πx sin2 2 L2 (2n + 1)2 π 2 L

L 32A2 ρc2 . + 1)2 π 2 2

L2 (2n

Therefore E=

∞ 

E2n+1 =

n=0

∞ 1 16A2 ρc2  2A2 ρc2 . = 2 2 π L n=0 (2n + 1) L

When the mid-point of the string has been displaced sideways by y ( L), the net (resolved) restoring force is 2T [y/(L/2)] = 4T y/L. Thus the total work done to produce a displacement of A is  A 2T A2 2ρc2 A2 4T y dy = = , W = L L L 0 i.e. the same as the total energy of the subsequent motion. 11.15 Prove that the potential for ρ < a associated with a vertical split cylinder of radius a, the two halves of which (cos φ > 0 and cos φ < 0) are maintained at equal and opposite potentials ±V , is given by u(ρ, φ) =

∞ 4V  (−1)n  ρ 2n+1 cos(2n + 1)φ. π n=0 2n + 1 a

The most general solution of the Laplace equation in cylindrical polar coordinates that is independent of z is T (ρ, φ) = C ln ρ + D +

∞ 

(An cos nφ + Bn sin nφ)(Cn ρ n + Dn ρ −n ).

n=1

The required potential must be single-valued and finite in the space inside the cylinder (which includes ρ = 0), and on the cylinder it must take the boundary values u = V for cos φ > 0 and u = −V for cos φ < 0, i.e the boundary-value function is a square-wave function with average value zero. Although the function is antisymmetric in cos φ, it is symmetric in φ and so the solution will contain only cosine terms (and no sine terms). These considerations already determine that C = D = Bn = Dn = 0, and so have reduced the solution to the form u(ρ, φ) =

∞  n=1

An ρ n cos nφ.

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Solution methods for PDEs

On ρ = a this must match the stated boundary conditions, and so we are faced with a Fourier cosine series calculation. Multiplying through by cos mφ and integrating yields  π/2  π m 1 2π = 2 Am a V cos mφ dφ + 2 (−V ) cos mφ dφ 2 0 π/2     sin mφ π sin mφ π/2 − 2V = 2V m m 0 π/2   2V mπ mπ = sin + sin m 2 2 4V = (−1)(m−1)/2 for m odd, = 0 for m even. m Writing m = 2n + 1 gives the solution as u(ρ, φ) =

∞ 4V  (−1)n  ρ 2n+1 cos(2n + 1)φ. π n=0 2n + 1 a

11.17 Two identical copper bars are each of length a. Initially, one is at 0 ◦ C and the other at 100 ◦ C; they are then joined together end to end and thermally isolated. Obtain in the form of a Fourier series an expression u(x, t) for the temperature at any point a distance x from the join at a later time t. Bear in mind the heat flow conditions at the free ends of the bars. Taking a = 0.5 m estimate the time it takes for one of the free ends to attain a temperature of 55 ◦ C. The thermal conductivity of copper is 3.8 × 102 J m−1 K−1 s−1 , and its specific heat capacity is 3.4 × 106 J m−3 K−1 .

The equation governing the heat flow is k

∂ 2u ∂u =s , ∂x 2 ∂t

which is the diffusion equation with diffusion constant κ = k/s = 3.8 × 102 /3.4 × 106 = 1.12 × 10−4 m2 s−1 . Making the usual separation of variables substitution shows that the time variation is 2 of the form T (t) = T (0)e−κλ t when the spatial solution is a sinusoidal function of λx. The final common temperature is 50 ◦ C and we make this explicit by writing the general solution as  2 u(x, t) = 50 + (Aλ sin λx + Bλ cos λx)e−κλ t . λ

This term having been taken out, the summation must be antisymmetric about x = 0 and therefore contain no cosine terms, i.e. Bλ = 0. The boundary condition is that there is no heat flow at x = ±a; this means that ∂u/∂x = 0 at these points and requires λAλ cos λx|x=±a = 0



λa = (n + 12 )π



λ=

(2n + 1)π , 2a

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Solution methods for PDEs

where n is an integer. This corresponds to a fundamental Fourier period of 4a. The solution thus takes the form   ∞  (2n + 1)πx (2n + 1)2 π 2 κt u(x, t) = 50 + . An sin exp − 2 2a 4a n=0 At t = 0, the sum must take the values +50 for 0 < x < 2a and −50 for −2a < x < 0. This is (yet) another square-wave function – one that is antisymmetric about x = 0 and has amplitude 50. The calculation will not be repeated here but gives An = 200/[(2n + 1)π], making the complete solution   ∞ (2n + 1)πx (2n + 1)2 π 2 κt 200  1 sin exp − . u(x, t) = 50 + π n=0 2n + 1 2a 4a 2 For a free end, where x = a and sin[(2n + 1)πx/2a] = (−1)n , to attain 55 ◦ C needs   ∞  (2n + 1)2 π 2 1.12 × 10−4 5π (−1)n exp − t = = 0.0785. 2n + 1 4 × 0.25 200 n=0 In principle this is an insoluble equation but, because the RHS  1, the n = 0 term alone will give a good approximation to t: exp(−1.105 × 10−3 t) ≈ 0.0785



t ≈ 2300 s.

11.19 For an infinite metal bar that has an initial (t = 0) temperature distribution f (x) along its length, the temperature distribution at a general time t can be shown to be given by    ∞ (x − ξ )2 1 f (ξ ) dξ. exp − u(x, t) = √ 4κt 4πκt −∞ Find an explicit expression for u(x, t) given that f (x) = exp(−x 2 /a 2 ).

The given initial distribution is f (ξ ) = exp(−ξ 2 /a 2 ) and so    2  ∞ (x − ξ )2 1 ξ exp − u(x, t) = √ exp − 2 dξ. 4κt a 4πκt −∞ Now consider the exponent in the integrand, writing 1 +

4κt as τ 2 for compactness: a2

ξ 2 τ 2 − 2ξ x + x 2 4κt (ξ τ − xτ −1 )2 − x 2 τ −2 + x 2 =− 4κt 2 −2 τ − x2 x , defining η, ≡ −η2 + 4κt τ dξ with dη = √ . 4κt

exponent = −

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Solution methods for PDEs

With a change of variable from ξ to η, the integral becomes √  ∞  2 −2 1 4κt x τ − x2 2 u(x, t) = √ exp(−η ) dη exp 4κt τ 4πκt −∞   1 1 1 − τ2 √ π = √ exp x 2 4κt τ 2 πτ   a x2 = √ . exp − 2 a + 4κt a 2 + 4κt In words, although it retains a Gaussian shape, the initial distribution spreads symmetrically about the origin, its variance increasing linearly with time (a 2 → a 2 + √ 4κt). As is typical with diffusion processes, for large enough times the width varies as t. 11.21 In the region −∞ < x, y < ∞ and −t ≤ z ≤ t, a charge-density wave ρ(r) = A cos qx, in the x-direction, is represented by  ∞ eiqx iαz ρ(r) = √ ρ(α)e ˜ dα. 2π −∞ The resulting potential is represented by eiqx V (r) = √ 2π





V˜ (α)eiαz dα.

−∞

Determine the relationship between V˜ (α) and ρ(α), ˜ and hence show that the potential at the point (0, 0, 0) is given by  ∞ sin kt A dk. π 0 −∞ k(k 2 + q 2 )

Poisson’s equation, ∇ 2 V (r) = −

ρ(r) , 0

provides the link between a charge density and the potential it produces. Taking V (r) in the form of its Fourier representation gives ∇ 2 V as  ∞ ∂ 2 V (r) ∂ 2 V (r) ∂ 2 V (r) eiqx + + =√ (−q 2 − α 2 )V˜ (α)eiαz dα, ∂x 2 ∂y 2 ∂z2 2π −∞ with the −q 2 arising from the x-differentiation and the −α 2 from the z-differentiation; the ∂ 2 V /∂y 2 term contributes nothing. Comparing this with the integral expression for −ρ(r)/ 0 shows that −ρ(α) ˜ = 0 (−q 2 − α 2 )V˜ (α). With the charge-density wave confined in the z-direction to −t ≤ z ≤ t, the expression for ρ(r) in Cartesian coordinates is (in terms of Heaviside functions) ρ(r) = Aeiqx [H (z + t) − H (z − t)].

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Solution methods for PDEs

The Fourier transform ρ(α) ˜ is therefore given by ρ(α) ˜ = = = = V (x, 0, z) =

Now,

= ⇒

V (0, 0, 0) =

 ∞ 1 A[H (z + t) − H (z − t)] e−iαz dz √ 2π −∞  t A e−iαz dz √ 2π −t A e−iαt − eiαt √ −iα 2π A 2 sin αt . √ α 2π  ∞ ρ(α) ˜ eiqx eiαz dα √ 2π −∞ 0 (q 2 + α 2 )  ∞ A 2 sin αt eiαz eiqx dα, √ √ 2 + α2) (q α 2π −∞ 0 2π  ∞ A sin αt dα, π 0 −∞ α(α 2 + q 2 )

as stated in the question. 11.23 Find the Green’s function G(r, r0 ) in the half-space z > 0 for the solution of ∇ 2  = 0 with  specified in cylindrical polar coordinates (ρ, φ, z) on the plane z = 0 by  1 for ρ ≤ 1, (ρ, φ, z) = 1/ρ for ρ > 1. Determine the variation of (0, 0, z) along the z-axis.

For the half-space z > 0 the bounding surface consists of the plane z = 0 and the (hemi-spherical) surface at infinity; the Green’s function must take zero value on these surfaces. In order to ensure this when a unit point source is introduced at r = y, we must place a compensating negative unit source at y’s reflection point in the plane. If, in cylindrical polar coordinates, y = (ρ, φ, z0 ), then the image charge has to be at y = (ρ, φ, −z0 ). The resulting Green’s function G(x, y) is given by G(x, y) = −

1 1 + . 4π|x − y| 4π|x − y |

The solution to the problem with a given potential distribution f (ρ, φ) on the z = 0 part of the bounding surface S is given by   ∂G ρ dφ dρ, (y) = f (ρ, φ) − ∂z S 

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Solution methods for PDEs

the minus sign arising because the outward normal to the region is in the negative zdirection. Calculating these functions explicitly gives 1 1 + , 4π[ρ 2 + (z − z0 )2 ]1/2 4π[ρ 2 + (z + z0 )2 ]1/2 (z + z0 ) z − z0 ∂G − , = ∂z 4π[ρ 2 + (z − z0 )2 ]3/2 4π[ρ 2 + (z + z0 )2 ]3/2  ∂G  −2z0 − =− . ∂z z=0 4π[ρ 2 + z02 ]3/2 G(x, y) = −

Substituting the various factors into the general integral gives  ∞ 2z0 f (ρ) 2π ρ dρ (0, 0, z0 ) = 2 + z2 ]3/2 4π[ρ 0 0  1  ∞ z0 ρ z0 = dρ + dρ 2 3/2 2 2 (ρ + z02 )3/2 0 (ρ + z0 ) 1  π/2 2 2  2 z0 sec u 2 −1/2 1 + du, = −z0 (ρ + z0 ) 0 z03 sec3 u θ where, in the second integral, we have set ρ = z0 tan u with dρ = z0 sec2 u du and θ = tan−1 (1/z0 ). The integral can now be obtained in closed form as z0 1 π/2 + 1 + [ sin u ]θ z0 (1 + z02 )1/2 z0 1 1 =1− + − . 2 1/2 z0 z0 (1 + z02 )1/2 (1 + z0 )

(0, 0, z0 ) = −

Thus the variation of  along the z-axis is given by (0, 0, z) =

z(1 + z2 )1/2 − z2 + (1 + z2 )1/2 − 1 . z(1 + z2 )1/2

11.25 Find, in the form of an infinite series, the Green’s function of the ∇ 2 operator for the Dirichlet problem in the region −∞ < x < ∞, −∞ < y < ∞, −c ≤ z ≤ c.

The fundamental solution in three dimensions of ∇ 2 ψ = δ(r) is ψ(r) = −1/(4πr). For the given problem, G(r, r0 ) has to take the value zero on z = ±c and → 0 for |x| → ∞ and |y| → ∞. Image charges have to be added in the regions z > c and z < −c to bring this about after a charge q has been placed at r0 = (x0 , y0 , z0 ) with −c < z0 < c. Clearly all images will be on the line x = x0 , y = y0 . Each image placed at z = ξ in the region z > c will require a further image of the same strength but opposite sign at z = −c − ξ (in the region z < −c) so as to maintain the plane z = −c as an equipotential. Likewise, each image placed at z = −χ in the region z < −c will require a further image of the same strength but opposite sign at z = c + χ (in the region z > c) so as to maintain the plane z = c as an equipotential. Thus successive

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Solution methods for PDEs

image charges appear as follows: −q +q −q +q

2c − z0 −3c + z0 4c − z0 etc.

−2c − z0 3c + z0 −4c − z0 etc.

The terms in the Green’s function that are additional to the fundamental solution, −

1 [(x − x0 )2 + (y − y0 )2 + (z − z0 )2 ]−1/2 , 4π

are therefore −

∞  (−1)n (−1)  4π n=2 [(x − x0 )2 + (y − y0 )2 + (z + (−1)n z0 − nc)2 ]1/2

 (−1)n . + [(x − x0 )2 + (y − y0 )2 + (z + (−1)n z0 + nc)2 ]1/2

11.27 Determine the Green’s function for the Klein–Gordon equation in a half-space as follows. (a) By applying the divergence theorem to the volume integral   φ(∇ 2 − m2 )ψ − ψ(∇ 2 − m2 )φ dV , V

obtain a Green’s function expression, as the sum of a volume integral and a surface integral, for the function φ(r ) that satisfies ∇ 2 φ − m2 φ = ρ in V and takes the specified form φ = f on S, the boundary of V . The Green’s function, G(r, r ), to be used satisfies ∇ 2 G − m2 G = δ(r − r ) and vanishes when r is on S. (b) When V is all space, G(r, r ) can be written as G(t) = g(t)/t, where t = |r − r | and g(t) is bounded as t → ∞. Find the form of G(t). (c) Find φ(r) in the half-space x > 0 if ρ(r) = δ(r − r1 ) and φ = 0 both on x = 0 and as r → ∞.

(a) For general φ and ψ we have 







φ(∇ − m )ψ − ψ(∇ − m )φ dV = 2

2

2

2

V

=

V V

φ∇ 2 ψ − ψ∇ 2 φ dV



∇ · (φ∇ψ − ψ∇φ) dV (φ∇ψ − ψ∇φ) · n dS.

= S

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Solution methods for PDEs

Now take φ as φ, with ∇ 2 φ − m2 φ = ρ and φ = f on the surface S, and ψ as G(r, r ) with ∇ 2 G − m2 G = δ(r − r ) and G(r, r ) = 0 on S:   [φ(r)δ(r − r ) − G(r, r )ρ(r)] dV = [f (r)∇G(r, r ) − 0] · n dS, V

S

which, on rearrangement, gives   φ(r ) = G(r, r )ρ(r) dV + f (r)∇G(r, r ) · n dS. V

S

(b) In the following calculation we start by formally integrating the defining Green’s equation, ∇ 2 G − m2 G = δ(r − r ), over a sphere of radius t centered on r . Having replaced the volume integral of ∇ 2 G with the corresponding surface integral given by the divergence theorem, we move the origin to r , denote |r − r | by t and integrate both sides of the equation from t = 0 to t = t:    2 2 ∇ G dV − m G dV = δ(r − r ) dV, V V V   2 ∇G · n dS − m G dV = 1, S V  t dG 2 G(t )4πt dt = 1, (∗) 4πt 2 − m2 dt 0 4πt 2 G + 8πtG − 4πm2 t 2 G = 0, from differentiating w.r.t. t, tG + 2G − m2 tG = 0. With G(t) = g(t)/t, G = −

g g + t2 t

and

G =

2g 2g g − + , t3 t2 t

and the equation becomes 2g 2g 2g 2g − − + + g − m2 g, t2 t t2 t 0 = g − m2 g,

0= ⇒

g(t) = Ae−mt , since g is bounded as t → ∞.

The value of A is determined by resubstituting into (∗), which then reads    t Ae−mt mAe−mt Ae−mt 2 4πt dt = 1, − m2 4πt 2 − 2 − t t t 0   −mt 1 − e−mt te −mt 2 −4πAe (1 + mt) − 4πAm − + = 1, m m2 −4πA = 1,

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Solution methods for PDEs

making the solution e−mt , where t = |r − r |. 4πt (c) For the situation in which ρ(r) = δ(r − r1 ), i.e. a unit positive charge at r1 = (x1 , y1 , z1 ), and φ = 0 on the plane x = 0, we must have a unit negative image charge at r2 = (−x1 , y1 , z1 ). The solution in the region x > 0 is then   e−m|r−r2 | 1 e−m|r−r1 | − . φ(r) = − 4π |r − r1 | |r − r2 | G(r, r ) = −

12

Calculus of variations

12.1 A surface of revolution, whose equation in cylindrical polar coordinates is ρ = ρ(z), is bounded by the  circles ρ = a, z = ±c (a > c). Show that the function that makes the surface integral I = ρ −1/2 dS stationary with respect to small variations is given by ρ(z) = k + z2 /(4k), where k = [a ± (a 2 − c2 )1/2 ]/2.

The surface element lying between z and z + dz is given by dS = 2πρ [(dρ)2 + (dz)2 ]1/2 = 2πρ (1 + ρ )1/2 dz 2

and the integral to be made stationary is   −1/2 I= ρ dS = 2π

c

−c

ρ −1/2 ρ (1 + ρ )1/2 dz. 2

The integrand F (ρ , ρ, z) does not in fact contain z explicitly, and so a first integral of the EL equation, symbolically given by F − ρ ∂F /∂ρ = k, is   ρ 1/2 ρ 1/2 2 1/2 ρ (1 + ρ ) − ρ = A, (1 + ρ 2 )1/2 ρ 1/2 = A. (1 + ρ 2 )1/2 On rearrangement and subsequent integration this gives 1/2  dρ ρ − A2 , = dz A2   dz dρ  = , A ρ − A2  z 2 ρ − A2 = + C. A Now, ρ(±c) = a implies both that C = 0 and that a − A2 = 4k 2 − 4ka + c2 = 0



k = 12 [a ± (a 2 − c2 )1/2 ].

The two stationary functions are therefore ρ= 166

c2 . Thus, writing A2 as k, 4A2

z2 + k, 4k

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Calculus of variations

with k as given above. A simple sketch shows that the positive sign in k corresponds to a smaller value of the integral. 12.3 The refractive index n of a medium is a function only of the distance r from a fixed point O. Prove that the equation of a light ray, assumed to lie in a plane through O, traveling in the medium satisfies (in plane polar coordinates)   r 2 n2 (r) 1 dr 2 = 2 2 − 1, 2 r dφ a n (a) where a is the distance of the ray from O at the point at which dr/dφ = 0. If n = [1 + (α 2 /r 2 )]1/2 and the ray starts and ends far from O, find its deviation (the angle through which the ray is turned), if its minimum distance from O is a.

An element of path length is ds = [(dr)2 + (r dφ)2 ]1/2 and the time taken for the light to traverse it is n(r) ds/c, where c is the speed of light in vacuo. Fermat’s principle then implies that the light follows the curve that minimizes  T =

n(r) ds = c



n(r 2 + r 2 )1/2 dφ, c

where r = dr/dφ. Since the integrand does not contain φ explicitly, the EL equation integrates to (see Problem 12.1) n(r + r 2 )1/2 − r 2

nr = A, (r + r 2 )1/2 nr 2 = A. (r 2 + r 2 )1/2 2

Since r = 0 when r = a, A = n(a)a 2 /a, and the equation is as follows: a 2 n2 (a)(r + r 2 ) = n2 (r)r 4 , n2 (r)r 4 2 r = 2 − r 2, n (a)a 2   n2 (r)r 2 1 dr 2 = − 1. ⇒ r 2 dφ n2 (a)a 2 2

If n(r) = [1 + (α/r)2 ]1/2 , the minimizing curve satisfies 



dr dφ

2

dφ (a 2 + α 2 )1/2

r 2 (r 2 + α 2 ) − r2 a2 + α2 r 2 (r 2 − a 2 ) = , a2 + α2 dr =± √ . r r 2 − a2 =

168

Calculus of variations

By symmetry, φ φ final − φ initial ≡ (a 2 + α 2 )1/2 (a 2 + α 2 )1/2  ∞ dr =2 , set r = a cosh ψ √ r r 2 − a2 a ∞ a sinh ψ dψ =2 2 a cosh ψ sinh ψ 0 ∞ 2 = sech ψ dψ, set eψ = z a 0  2 ∞ z−1 dz = a 1 12 (z + z−1 )  2 ∞ 2 dz = a 1 z2 + 1 4  −1 ∞ tan z 1 = a  π π 4 π − = . = a 2 4 a If the refractive index were everywhere unity (α = 0), φ would be π (no deviation). Thus the deviation is given by π 2 (a + α 2 )1/2 − π. a 12.5 Prove the following results about general systems. (a) For a system described in terms of coordinates qi and t, show that if t does not appear explicitly in the expressions for x, y and z (x = x(qi , t), etc.) then the kinetic energy  T is a homogeneous quadratic function of the q˙i (it may also involve the qi ). Deduce that i q˙i (∂T /∂ q˙i ) = 2T . (b) Assuming that the forces acting on the system are derivable from a potential V , show, by expressing dT /dt in terms of qi and q˙i , that d(T + V )/dt = 0.

To save space we will use the summation convention for summing over the index of the qi . (a) The space variables x, y and z are not explicit functions of t and the kinetic energy, T , is given by T = 12 (αx x˙ 2 + αy y˙ 2 + αz z˙ 2 )   2  2  2  1 ∂x ∂y ∂z = q˙i + αy q˙j + αz q˙k αx 2 ∂qi ∂qj ∂qk = Amn q˙m q˙n , with Amn

  1 ∂x ∂x ∂y ∂y ∂z ∂z αx = + αy + αz = Anm . 2 ∂qm ∂qn ∂qm ∂qn ∂qm ∂qn

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Calculus of variations

Hence T is a homogeneous quadratic function of the q˙i (though the Amn may involve the qi ). Further, ∂T = Ain q˙n + Ami q˙m = 2Ami q˙m ∂ q˙i ∂T and q˙i = 2q˙i Ami q˙m = 2T . ∂ q˙i (b) The Lagrangian is L = T − V , with T = T (qi , q˙i ) and V = V (qi ). Thus dT dT ∂T q˙i + q¨i = dt ∂qi d q˙i Hamilton’s principle requires that   d ∂L = dt ∂ q˙i   d ∂T ⇒ = dt ∂ q˙i

and

dV ∂V q˙i . = dt ∂qi

(∗)

∂L , ∂qi ∂T ∂V − . ∂qi ∂qi

(∗∗)

But, from part (a), 2T = q˙i

∂T , ∂ q˙i

  ∂T d ∂T d + q˙i (2T ) = q¨i dt ∂ q˙i dt ∂ q˙i ∂T ∂T ∂V = q¨i + q˙i − q˙i , using (∗∗), ∂ q˙i ∂qi ∂qi dT dV = − , using (∗). dt dt This can be rearranged as d (T + V ) = 0. dt 12.7 In cylindrical polar coordinates, the curve (ρ(θ ), θ, αρ(θ )) lies on the surface of the cone z = αρ. Show that geodesics (curves of minimum length joining two points) on the cone satisfy ρ 4 = c2 [β 2 ρ + ρ 2 ], 2

where c is an arbitrary constant, but β has to have a particular value. Determine the form of ρ(θ ) and hence find the equation of the shortest path on the cone between the points (R, −θ0 , αR) and (R, θ0 , αR). [You will find it useful to determine the form of the derivative of cos−1 (u−1 ).]

In cylindrical polar coordinates the element of length is given by (ds)2 = (dρ)2 + (ρ dθ)2 + (dz)2 ,

170

Calculus of variations

and the total length of a curve between two points parameterized by θ0 and θ1 is ,  2  θ1  2 dρ dz 2 s= +ρ + dθ dθ dθ θ0 ,  2  θ1 dρ 2 2 = ρ + (1 + α ) dθ, since z = αρ. dθ θ0 Since the independent variable θ does not occur explicitly in the integrand, a first integral of the EL equation is  (1 + α 2 )ρ ρ 2 + (1 + α 2 )ρ 2 − ρ  = c. ρ 2 + (1 + α 2 )ρ 2 After being multiplied through by the square root, this can be arranged as follows:  2 2 ρ 2 + (1 + α 2 )ρ − (1 + α 2 )ρ = c ρ 2 + (1 + α 2 )ρ 2 , ρ 4 = c2 [ρ 2 + (1 + α 2 )ρ ]. 2

This is the given equation of the geodesic, in which c is arbitrary but β 2 must have the value 1 + α 2 . Guided by the hint, we first determine the derivative of y(u) = cos−1 (u−1 ): −1 −1 dy 1 =√ . = √ 2 du 1 − u−2 u u u2 − 1 Now, returning to the geodesic, rewrite it as ρ 4 − c2 ρ 2 = c2 β 2 ρ , dρ ρ(ρ 2 − c2 )1/2 = cβ . dθ 2

Setting ρ = cu, du , dθ β du dθ = , 2 u(u − 1)1/2

uc2 (u2 − 1)1/2 = c2 β

which integrates to θ = β cos−1

  1 + k, u

using the result from the hint. Since the geodesic must pass through both (R, −θ0 , αR) and (R, θ0 , αR), we must have k = 0 and cos

θ0 c = . β R

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Calculus of variations

Further, at a general point on the geodesic, cos

θ c = . β ρ

Eliminating c then shows that the geodesic on the cone that joins the two given points is ρ(θ) =

R cos(θ0 /β) . cos(θ/β)

12.9 You are provided with a line of length πa/2 and negligible mass and some lead shot of total mass M. Use a variational method to determine how the lead shot must be distributed along the line if the loaded line is to hang in a circular arc of radius a when its ends are attached to two points at the same height. Measure the distance s along the line from its center.

We first note that the total mass of shot available is merely a scaling factor and not a constraint on the minimization process. The length of string is sufficient to form one-quarter of a complete circle of radius a, √ and so the ends of the string must be fixed to points that are 2a sin(π/4) = 2a apart. to minimize the integral  We take the distribution of shot as ρ = ρ(s)  and have √ gy(s)ρ(s) ds, but subject to the requirement dx = a/ 2. Expressed as an integral over s, this requirement can be written  s=πa/4  πa/4 a 2 dx = (1 − y )1/2 ds, √ = 2 s=0 0 where the derivative y of y is with respect to s (not x). We therefore consider the minimization of F (y, y , s) ds, where  F (y, y , s) = gyρ + λ 1 − y 2 . The EL equation takes the form

d λ ds



d ds



∂F ∂y

−y

 = 

∂F , ∂y

 = gρ(s), 1 − y 2  s −λy  = gρ(s ) ds ≡ gP (s), 0 1 − y 2

since y (0) = 0 by symmetry. Now we require P (s) to be such that the solution to this equation takes the form of an arc of a circle, y(s) = y0 − a cos(s/a). If this is so, then y (s) = sin(s/a) and −λ sin(s/a) = gP (s). cos(s/a)

172

Calculus of variations

When s = πa/4, P (s) must have the value M/2, implying that λ = −Mg/2 and that, consequently, s  M P (s) = tan . 2 a The required distribution ρ(s) is recovered by differentiating this to obtain s  M dP = sec2 . ρ(s) = ds 2a a 12.11 A general result is that light travels through a variable medium by a path that minimizes the travel time (this is an alternative formulation of Fermat’s principle). With respect to a particular cylindrical polar coordinate system (ρ, φ, z), the speed of light v(ρ, φ) is independent of z. If the path of the light is parameterized as ρ = ρ(z), φ = φ(z), show that v 2 (ρ + ρ 2 φ + 1) 2

2

is constant along the path. For the particular case when v = v(ρ) = b(a 2 + ρ 2 )1/2 , show that the two Euler–Lagrange equations have a common solution in which the light travels along a helical path given by φ = Az + B, ρ = C, provided that A has a particular value.

In cylindrical polar coordinates with ρ = ρ(z) and φ = φ(z),   2  2 1/2 dρ 2 dφ ds = 1 + +ρ dz. dz dz The total travel time of the light is therefore given by  (1 + ρ 2 + ρ 2 φ 2 )1/2 τ= dz. v(ρ, φ) Since z does not appear explicitly in the integrand, we have from the general first integral of the EL equations for more than one dependent variable that 1 1 ρ 2 ρ2φ 2 (1 + ρ 2 + ρ 2 φ 2 )1/2 − = k. − v(ρ, φ) v (1 + ρ 2 + ρ 2 φ 2 )1/2 v (1 + ρ 2 + ρ 2 φ 2 )1/2 Rearranging this gives 1 + ρ + ρ 2 φ − ρ − ρ 2 φ = kv(1 + ρ + ρ 2 φ )1/2 , 2

2

2

2

2

2

1 = kv(1 + ρ + ρ 2 φ )1/2 , 2



2

v 2 (1 + ρ + ρ 2 φ ) = c, along the path. 2

2

Denoting (1 + ρ 2 + ρ 2 φ 2 ) by (∗∗) for brevity, the EL equations for ρ and φ are, respectively,   d ρ (∗∗)1/2 ∂v ρφ 2 = , (1) − v(∗∗)1/2 v 2 ∂ρ dz v(∗∗)1/2  2  (∗∗)1/2 ∂v d ρ φ and − = . (2) v 2 ∂φ dz v(∗∗)1/2

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Calculus of variations

Now, if v = b(a 2 + ρ 2 )1/2 , the only dependence on z in a possible solution φ = Az + B with ρ = C is through the first of these equations. To see this we note that the square brackets on the RHSs of the two EL equations do not contain any undifferentiated φ-terms and so the derivatives (with respect to z) of both are zero. Since ∂v/∂φ is also zero, equation (2) is identically satisfied as 0 = 0. This leaves only (1), which reads CA2 (1 + 0 + C 2 A2 )1/2 bC − = 0. b(a 2 + C 2 )1/2 (1 + 0 + C 2 A2 )1/2 b2 (a 2 + C 2 )(a 2 + C 2 )1/2 This is satisfied provided A2 (a 2 + C 2 ) = 1 + C 2 A2 , i.e. A = a −1 . Thus, a solution in the form of a helix is possible provided that the helix has a particular pitch, 2πa. 12.13 The Schwarzchild metric for the static field of a non-rotating spherically symmetric black hole of mass M is given by   2GM (dr)2 (ds)2 = c2 1 − 2 (dt)2 − − r 2 (dθ )2 − r 2 sin2 θ (dφ)2 . c r 1 − 2GM/(c2 r) Considering only motion confined  to the plane θ = π/2, and assuming that the path of a small test particle is such as to make ds stationary, find two first integrals of the equations of motion. From their Newtonian limits, in which GM/r, r˙ 2 and r 2 φ˙ 2 are all  c2 , identify the constants of integration.

For motion confined to the plane θ = π/2, dθ = 0 and the corresponding term in the metric can be ignored. With this simplification, we can write 

 ds =

c

2

2GM 1− 2 c r



r˙ 2 − − r 2 φ˙ 2 1 − (2GM)/(c2 r)

1/2 dt.

Writing the terms in braces as {∗∗}, the EL equation for φ reads   d −r 2 φ˙ − 0 = 0, dt {∗∗}1/2 r 2 φ˙ ⇒ = A. {∗∗}1/2 In the Newtonian limit {∗∗} → c2 and the equation becomes r 2 φ˙ = Ac. Thus, Ac is a measure of the angular momentum of the particle about the origin. The EL equation for r is more complicated but, because ds does not contain t explicitly, we can use the general result for the first integral of the EL equations when there is more  ∂F than one dependent variable: F − = k. This gives us a second equation as q˙i ∂ q˙i i

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Calculus of variations

follows: ∂F ∂F − φ˙ = B, ∂ r˙ ∂ φ˙ φ˙ r˙ + r 2 φ˙ = B. 2 [1 − (2GM)/(c r)] {∗∗}1/2 F − r˙

{∗∗}1/2 +

r˙ {∗∗}1/2

Multiplying through by {∗∗}1/2 and canceling the terms in r˙ 2 and φ˙ 2 now gives c2 −

 1/2 r˙ 2 2GM 2GM 2 ˙2 = B c2 − − − r φ . r r [1 − (2GM)/(c2 r)]

In the Newtonian limits, in which GM/r, r˙ 2 and r 2 φ˙ 2 are all  c2 , the equation can be rearranged and the braces expanded to first order in small quantities to give −1/2   2GM 2GM r˙ 2 2 2 2 ˙2 , B= c − c − − −r φ r r [1 − (2GM)/(c2 r)] 2GM c2 r 2 φ˙ 2 c2 GM c2 r˙ 2 + ··· , cB = c2 − + 2 + 2 + r c r 2c 2c2 GM 1 = c2 − + (˙r 2 + r 2 φ˙ 2 ) + · · · , r 2 which can be read as “total energy = rest mass energy + gravitational energy + radial and azimuthal kinetic energy”. Thus Bc is a measure of the total energy of the test particle. 12.15 Determine the minimum value that the integral  1 [x 4 (y )2 + 4x 2 (y )2 ] dx J = 0

can have, given that y is not singular at x = 0 and that y(1) = y (1) = 1. Assume that the Euler– Lagrange equation gives the lower limit.

We first set y (x) = u(x) with u(1) = y (1) = 1. The integral then becomes  1 [x 4 (u )2 + 4x 2 u2 ] dx. (∗) J = 0

This will be stationary if (using the EL equation) d (2x 4 u ) − 8x 2 u = 0, dx 8x 3 u + 2x 4 u − 8x 2 u = 0, x 2 u + 4xu − 4u = 0. As this is a homogeneous equation, we try u(x) = Ax n , obtaining n(n − 1) + 4n − 4 = 0



n = −4, or n = 1.

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Calculus of variations

The form of y (x) is thus y (x) = u(x) =

A + Bx x4

with

A + B = 1.

Further, y(x) = −

Bx 2 A + + C. 3x 3 2

Since y is not singular at x = 0 and y(1) = 1, we have that A = 0, B = 1 and C = 12 , yielding y(x) = 12 (1 + x 2 ). The minimal value of J is thus 

1

Jmin =

 [x (1) + 4x (x) ] dx = 4

2

2

2

0

0

1

 1 5x 4 dx = x 5 0 = 1.

12.17 Find an appropriate but simple trial function and use it to estimate the lowest eigenvalue λ0 of Stokes’ equation d 2y + λxy = 0, y(0) = y(π) = 0. dx 2 Explain why your estimate must be strictly greater than λ0 .

Stokes’ equation is an SL equation with p = 1, q = 0 and ρ = x. For the given boundary conditions the obvious trial function is y(x) = sin x. The lowest eigenvalue λ0 ≤ I /J , where  π  π π 2 I = py dx = cos2 x dx = 2 0 0  π  π and J = ρy 2 dx = x sin2 x dx 0

 =

0 π

0



x2 = 4 =

1 x(1 2

− cos 2x) dx





0

x sin 2x − 2 2

π 0

1 + 2



π 0

sin 2x dx 2

π2 . 4

Thus λ0 ≤ ( 12 π)/( 14 π 2 ) = 2/π. However, if we substitute the trial function directly into the equation we obtain − sin x +

2 x sin x = 0, π

which is clearly not satisfied. Thus the trial function is not an eigenfunction, and the actual lowest eigenvalue must be strictly less than the estimate of 2/π.

176

Calculus of variations

12.19 A drum skin is stretched across a fixed circular rim of radius a. Small transverse vibrations of the skin have an amplitude z(ρ, φ, t) that satisfies ∇ 2z =

1 ∂ 2z c2 ∂t 2

in plane polar coordinates. For a normal mode independent of azimuth, in which case z = Z(ρ) cos ωt, find the differential equation satisfied by Z(ρ). By using a trial function of the form a ν − ρ ν , with adjustable parameter ν, obtain an estimate for the lowest normal mode frequency. [The exact answer is (5.78)1/2 c/a.]

In cylindrical polar coordinates, (ρ, φ), the wave equation ∇ 2z =

1 ∂ 2z c2 ∂t 2

has azimuth-independent solutions (i.e. independent of φ) of the form z(ρ, t) = Z(ρ) cos ωt, and reduces to   dZ Zω2 1 d ρ cos ωt = − 2 cos ωt, ρ dρ dρ c   dZ ω2 d ρ + 2 ρZ = 0. dρ dρ c The boundary conditions require that Z(a) = 0 and, so that there is no physical discontinuity in the slope of the drum skin at the origin, Z (0) = 0. This is an SL equation with p = ρ, q = 0 and weight function w = ρ. A suitable trial function is Z(ρ) = a ν − ρ ν , which automatically satisfies Z(a) = 0 and, provided ν > 1, has Z (0) = −νρ ν−1 |ρ=0 = 0. We recall that the lowest eigenfrequency satisfies the general formula  a [(pZ )2 − qZ 2 ] dρ ω2 . ≤ 0  a c2 wZ 2 dρ 0

In this case

 ω2 ≤  c2

a

ρ ν 2 ρ 2ν−2 dρ 0 a

ρ(a ν − ρ ν )2 dρ

0



a

ν 2 ρ 2ν−1 dρ =

0 a

(ρa 0



− 2ρ ν+1 a ν + ρ 2ν+1 ) dρ

177

Calculus of variations

=

a 2ν+2 2

(ν 2 a 2ν )/2ν 2a 2ν+2 a 2ν+2 − + ν+2 2ν + 2

=

1 ν(ν + 2)(2ν + 2) 2 a (ν + 2)(2ν + 2) − 4(2ν + 2) + 2(ν + 2)

=

(ν + 2)(ν + 1) . νa 2

Since ν is an adjustable parameter and we know that, however we choose it, the resulting estimate can never be less than the lowest true eigenvalue, we choose the value that minimizes the above estimate. Differentiating the estimate with respect to ν gives √ ν(2ν + 3) − (ν 2 + 3ν + 2) = 0 ⇒ ν 2 − 2 = 0 ⇒ ν = 2. Thus the least upper bound to be found with this parameterization is √ √ c2 √ c2 ( 2 + 2)( 2 + 1) c = 2 ( 2 + 2)2 ⇒ ω = (5.83)1/2 . ω2 ≤ 2 √ 2 a 2a a As noted, the actual lowest eigenfrequency is very little below this. 12.21 For the boundary conditions given below, obtain a functional (y) whose stationary values give the eigenvalues of the equation (1 + x)

dy d 2y + (2 + x) + λy = 0, dx 2 dx

y(0) = 0, y (2) = 0.

Derive an approximation to the lowest eigenvalue λ0 using the trial function y(x) = xe−x/2 . For what value(s) of γ would y(x) = xe−x/2 + β sin γ x be a suitable trial function for attempting to obtain an improved estimate of λ0 ?

Since the derivative of 1 + x is not equal to 2 + x, the given equation is not in self-adjoint form and an integrating factor for the standard form equation, λy 2 + x dy d 2y + = 0, + dx 2 1 + x dx 1+x is needed. This will be  x   2+u exp du = exp 1+u

x



1 1+ 1+u



 du = ex (1 + x).

Thus, after multiplying through by this IF, the equation takes the SL form [(1 + x)ex y ] + λex y = 0, with p(x) = (1 + x)ex , q(x) = 0 and ρ(x) = ex .

178

Calculus of variations

The required functional is therefore 2 (y) =

0

[(1 + x)ex y 2 + 0] dx , 2 2 ex dx y 0

 2 provided that, for the eigenfunctions yi of the equation, yi p(x)yj (x) 0 = 0; this condition is automatically satisfied with the given boundary conditions. For the trial function y(x) = xe−x/2 , clearly y(0) = 0 and, less obviously, y (x) = (1 − 12 x)e−x/2 , making y (2) = 0. The functional takes the following form: 2

= = = =

2  (1 + x)ex 1 − 12 x e−x dx 2 2 −x x 0 x e e dx 2  2 1 0 (1 + x) 1 − 2 x dx 2 2 0 x dx 2  1 2 1 3 2 0 1 − x + 4 x + 4 x dx 8/3   3 3 8 16 3 2− + = . 8 4 3 16 8 0

Thus the lowest eigenvalue is ≤ 38 . We already know that xe−x/2 is a suitable trial function and thus y2 (x) = sin γ x can be considered on its own. It satisfies y2 (0) = 0, but must also satisfy y2 (2) = γ cos(2γ ) = 0. This requires that γ = 12 (n + 12 )π for some integer n; trial functions with γ of this form can be used to try to obtain a better bound on λ0 by choosing the best value for n and adjusting the parameter β. 12.23 The unnormalized ground-state (i.e. the lowest-energy) wavefunction of the simple harmonic oscilh. Take as a trial function the lator of classical frequency ω is exp(−αx 2 ), where α = mω/2− orthogonal wavefunction x 2n+1 exp(−αx 2 ), using the integer n as a variable parameter, and apply either Sturm–Liouville theory or the Rayleigh–Ritz principle to show that the energy of the second lowest state of a quantum harmonic oscillator is ≤ 3− hω/2.

We first note that, for n a non-negative integer,  ∞ 2 2 x 2n+1 e−αx e−αx dx = 0 −∞

on symmetry grounds and so confirm that the ground-state wavefunction, exp(−αx 2 ), and the trial function, ψ2n+1 = x 2n+1 exp(−αx 2 ), are orthogonal with respect to a unit weight function. The Hamiltonian for the quantum harmonic oscillator in one dimension is given by H =−

−2

k h d2 + x2. 2 2m dx 2

179

Calculus of variations

This means that to prepare the elements required for a Rayleigh–Ritz analysis we will need to find the second derivative of the trial function and evaluate integrals with integrands of the form x n exp(−2αx 2 ). To this end, define  ∞ n−1 2 x n e−2αx dx, with recurrence relation In = In−2 . In = 4α −∞ Using Leibnitz’ formula shows that  d 2 ψ2n+1 = 2n(2n + 1)x 2n−1 + 2(2n + 1)(−2α)x 2n+1 2 dx 2 + (4α 2 x 2 − 2α)x 2n+1 e−αx  2 = 2n(2n + 1)x 2n−1 − 2(4n + 3)αx 2n+1 + 4α 2 x 2n+3 e−αx . Hence, we find that H  is given by −

−2

h 2m





x 2n+1 e−αx

−∞

2

d 2 ψ2n+1 k dx + 2 dx 2





x 2 x 4n+2 e−2αx dx 2

−∞

k h  2n(2n + 1)I4n − 2(4n + 3)αI4n+2 + 4α 2 I4n+4 + I4n+4 2m 2 !  −2  2 4α (4n + 3) k(4n + 3) h 2n(2n + 1)4α = I4n+2 − − 2(4n + 3)α + + , 2m 4n + 1 4α 8α =−

−2

where we have used the recurrence relation to express all integrals in terms of I4n+2 . This has been done because the denominator of the Rayleigh–Ritz quotient is this (same) normalization integral, namely  ∞ ∗ ψ2n+1 ψ2n+1 dx = I4n+2 . −∞

Thus, the estimate E2n+1 = H /I4n+2 is given by  −2  k(4n + 3) h α 16n2 + 8n − 16n2 − 16n − 3 + E2n+1 = − 2m 4n + 1 8α = Using ω2 =

−2

h α 8n + 3 k(4n + 3) + . 2m 4n + 1 8α

mω k and α = − then yields m 2h  − −  hω 8n + 3 hω 8n2 + 12n + 3 E2n+1 = + 4n + 3 = . 4 4n + 1 2 4n + 1

For non-negative integers n (the orthogonality requirement is not satisfied for non-integer values), this has a minimum value of 32 − hω when n = 0. Thus the second lowest energy level is less than or equal to this value. In fact, it is equal to this value, as can be shown by substituting ψ1 into H ψ = Eψ.

180

Calculus of variations

12.25 The upper and lower surfaces of a film of liquid, which has surface energy per unit area (surface tension) γ and density ρ, have equations z = p(x) and z = q(x), respectively. The film has a given volume V (per unit depth in the y-direction) and lies in the region −L < x < L, with p(0) = q(0) = p(L) = q(L) = 0. The total energy (per unit depth) of the film consists of its surface energy and its gravitational energy, and is expressed by # L L " E = 12 ρg −L (p 2 − q 2 ) dx + γ −L (1 + p 2 )1/2 + (1 + q 2 )1/2 dx. (a) Express V in terms of p and q. (b) Show that, if the total energy is minimized, p and q must satisfy p 2 q 2 − = constant. (1 + p 2 )1/2 (1 + q 2 )1/2 (c) As an approximate solution, consider the equations p = a(L − |x|),

q = b(L − |x|),

where a and b are sufficiently small that a 3 and b3 can be neglected compared with unity. Find the values of a and b that minimize E.

(a) The total volume constraint is given simply by  L [p(x) − q(x)] dx. V = −L

(b) To take account of the constraint, consider the minimization of E − λV , where λ is an undetermined Lagrange multiplier. The integrand does not contain x explicitly and so we have two first integrals of the EL equations, one for p(x) and the other for q(x). They are γp 1 2 2 = k1 ρg(p2 − q 2 ) + γ (1 + p )1/2 + γ (1 + q )1/2 − λ(p − q) − p 2 (1 + p 2 )1/2 and 1 γ q 2 2 = k2 . ρg(p2 − q 2 ) + γ (1 + p )1/2 + γ (1 + q )1/2 − λ(p − q) − q 2 (1 + q 2 )1/2 Subtracting these two equations gives q 2 p 2 − = constant. (1 + p 2 )1/2 (1 + q 2 )1/2 (c) If p = a(L − |x|),

q = b(L − |x|),

the derivatives of p and q only take the values ±a and ±b, respectively, and the volume constraint becomes  L V V = (a − b)(L − |x|) dx = (a − b)L2 ⇒ b = a − 2 . L −L

181

Calculus of variations

The total energy can now be expressed entirely in terms of a and the given parameters, as follows:  L 1 E = ρg (a 2 − b2 )(L − |x|)2 dx + 2γ L(1 + a 2 )1/2 + 2γ L(1 + b2 )1/2 2 −L 1 2L3 = ρg(a 2 − b2 ) + 2γ L(1 + 12 a 2 + 1 + 12 b2 ) + O(a 4 ) + O(b4 ) 2 3 " 2 #  2 # ρgL3 " 2  ≈ a − a − LV2 + 2γ L 2 + 12 a 2 + 12 a − LV2 3     V2 aV V2 ρgL3 2aV 2 . − 4 + 2γ L 2 + a − 2 + = 3 L2 L L 2L4 This is minimized with respect to a when 2ρgL3 V 2γ LV + 4γ La − = 0, 3L2 L2 ρgV V − ⇒ a= , 2 2L 6γ ρgV V . ⇒ b=− 2 − 2L 6γ As might be expected, | b | > | a | and there is more of the liquid below the z = 0 plane than there is above it.

13

Integral equations

13.1 Solve the integral equation





cos(xv)y(v) dv = exp(−x 2 /2)

0

for the function y = y(x) for x > 0. Note that for x < 0, y(x) can be chosen as is most convenient.

Since cos uv is an even function of v, we will make y(−v) = y(v) so that the complete integrand is also an even function of v. The integral I on the LHS can then be written as 1 I= 2





1 cos(xv)y(v) dv = Re 2 −∞





e −∞

ixv

1 y(v) dv = 2





eixv y(v) dv,

−∞

√ the last step following because y(v) is symmetric in v. The integral is now 2π × a Fourier transform, and it follows from the inversion theorem for Fourier transforms applied to 1 2





−∞

eixv y(v) dv = exp(−x 2 /2)

that  ∞ 2 2 e−u /2 e−iux du 2π −∞  1 ∞ −(u+ix)2 /2 −x 2 /2 e e dx = π −∞ 1√ 2 2π e−x /2 = π ' 2 −x 2 /2 = . e π

y(x) =

Although, as noted in the question, y(x) is arbitrary for x < 0, because its form in this range does not affect the value of the integral, for x > 0 it must have the form given. This is tricky to prove formally, but any second solution w(x) has to satisfy 



cos(xv)[y(v) − w(v)] dv = 0

0

for all x > 0. Intuitively, this implies that y(x) and w(x) are identical functions. 182

183

Integral equations

13.3 Convert

 f (x) = exp x +

x

(x − y)f (y) dy

0

into a differential equation, and hence show that its solution is (α + βx) exp x + γ exp(−x), where α, β, γ are constants that should be determined.

We differentiate the integral equation twice and obtain  x f (x) = ex + (x − x)f (x) + f (y) dy, 0

f (x) = ex + f (x).

Expressed in the usual differential equation form, this last equation is f (x) − f (x) = ex , for which the CF is f (x) = Aex + Be−x . Since the complementary function contains the RHS of the equation, we try as a PI f (x) = Cxex : Cxex + 2Cex − Cxex = ex



β = C = 12 .

The general solution is therefore f (x) = Aex + Be−x + 12 xex . The boundary conditions needed to evaluate A and B are constructed by considering the integral equation and its derivative(s) at x = 0, because with x = 0 the integral on the RHS contributes nothing. We have f (0) = e0 + 0 = 1 and



f (0) = e + 0 = 1 0

Solving these yields α = A =

3 4



A+B =1



A−B +

and γ = B =

1 4

1 2

= 1.

and makes the complete solution

f (x) = 34 ex + 14 e−x + 12 xex .

13.5 Solve for φ(x) the integral equation  φ(x) = f (x) + λ 0

1

 n    x y n φ(y) dy, + y x

where f (x) is bounded for 0 < x < 1 and − 12 < n < 12 , expressing your answer in terms of the 1 quantities Fm = 0 f (y)y m dy. (a) Give the explicit solution when λ = 1. (b) For what values of λ are there no solutions unless F±n are in a particular ratio? What is this ratio?

This equation has a symmetric degenerate kernel, and so we set φ(x) = f (x) + a1 x n + a2 x −n ,

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Integral equations

giving

 xn yn [ f (y) + a1 y n + a2 y −n ] dy + yn xn 0  1  1 f (y) n −n =x dy + x y n f (y) dy + a1 x n yn 0 0  1  1 + a2 x −n + a1 x −n y 2n dy + a2 x n y −2n dy 0 0     a2 a1 + x −n Fn + a2 + . = x n F−n + a1 + 1 − 2n 2n + 1

φ(x) − f (x) = λ



1



This is consistent with the assumed form of φ(x), provided     a2 a1 a1 = λ F−n + a1 + and a2 = λ Fn + a2 + . 1 − 2n 2n + 1 These two simultaneous linear equations can now be solved for a1 and a2 . (a) For λ = 1, the equations simplify and decouple to yield a2 = −(1 − 2n)F−n

and a1 = −(1 + 2n)Fn ,

respectively, giving as the explicit solution φ(x) = f (x) − (1 + 2n)Fn x n − (1 − 2n)F−n x −n . (b) For a general value of λ, (1 − λ)a1 −

λ a2 = λF−n , 1 − 2n

λ a1 + (1 − λ)a2 = λFn . 1 + 2n The case λ = 0 is trivial, with φ(x) = f (x), and so suppose that λ = 0. Then, after being divided through by λ, the equations can be written in the matrix and vector form Aa = F: ⎞ ⎛ 1 1     − 1 − ⎟ a1 ⎜ λ F−n 1 − 2n ⎟ ⎜ = . ⎠ a ⎝ 1 1 Fn 2 − −1 1 + 2n λ −

In general, this matrix equation will have no solution if |A| = 0. This will be the case if  2 1 1 = 0, −1 − λ 1 − 4n2 which, on rearrangement, shows that λ would have to be given by 1 1 . =1± √ λ 1 − 4n2 We note that this value for λ is real because n lies in the range − 12 < n < 12 . In fact −∞ < λ < 12 . Even for these two values of λ, however, if either Fn = F−n = 0 or the

185

Integral equations

matrix equation



⎞ 1     − ⎜ ± √1 − 4n2 a1 F−n 1 − 2n ⎟ ⎜ ⎟ = ⎝ ⎠ a 1 1 Fn 2 ±√ − 1 + 2n 1 − 4n2 is equivalent to two linear equations that are multiples of each other, there will still be a solution. In this latter case, we must have ' Fn 1 − 2n =∓ . F−n 1 + 2n 1

Again we note that, because of the range in which n lies, this ratio is real; this condition can, however, require any value in the range −∞ to ∞ for Fn /F−n . 13.7 The kernel of the integral equation 

b

ψ(x) = λ

K(x, y)ψ(y) dy a

has the form ∞ 

K(x, y) =

hn (x)gn (y),

n=0

where the hn (x) form a complete orthonormal set of functions over the interval [a, b]. (a) Show that the eigenvalues λi are given by |M − λ−1 I| = 0, where M is the matrix with elements



b

Mkj =

gk (u)hj (u) du. a

 (i) (i) If the corresponding solutions are ψ (i) (x) = ∞ n=0 an hn (x), find an expression for an . (b) Obtain the eigenvalues and eigenfunctions over the interval [0, 2π] if K(x, y) =

∞  1 cos nx cos ny. n n=1

(a) We write the ith eigenfunction as ψ (i) (x) =

∞ 

an(i) hn (x).

n=0

From the orthonormality of the hn (x), it follows immediately that  b (i) = hm (x)ψ (i) (x) dx. am a

(i) am (i)

However, the coefficients defined below, since the ψ

have to be found as the components of the eigenvectors a(i) are not initially known.

186

Integral equations

Substituting this assumed form of solution, we obtain  b ∞ ∞ ∞   (i) am hm (x) = λi hn (x)gn (y) al(i) hl (y) dy a

m=0

= λi



n=0

l=0

al(i) Mnl hn (x).

n,l

Since the {hn } are an orthonormal set, it follows that (i) = λi am

 n,l

al(i) Mnl δmn = λi

∞ 

Mml al(i) ,

l=0

(i) i.e. (M − λ−1 i I)a = 0.

Thus, the allowed values of λi are given by |M − λ−1 I| = 0, and the expansion coefficients (i) by the components of the corresponding eigenvectors. am (b) To make the set {hn (x) = cos nx} into a complete orthonormal set we need to add the set of functions {ην (x) = sin νx} and then normalize all the functions by multiplying √ them by 1/ π . For this particular kernel the general functions gn (x) are given by gn (x) = √ n−1 π cos nx. The matrix elements are then √  2π π 1 π Mkj = cos ku du = δkj , √ cos j u k k π 0 √  2π 1 π Mkν = cos ku du = 0. √ sin νu k π 0 Thus the matrix M is diagonal and particularly simple. The eigenvalue equation reads ∞   π

k

j =0

 (i) δkj − λ−1 i δkj aj = 0,

giving the immediate result that λk = k/π with ak(k) = 1 and all other aj(k) = aν(k) = 0. The eigenfunction corresponding to eigenvalue k/π is therefore 1 ψ (k) (x) = hk (x) = √ cos kx. π 13.9 For f (t) = exp(−t 2 /2), use the relationships of the Fourier transforms of f (t) and tf (t) to that of f (t) itself to find a simple differential equation satisfied by f˜(ω), the Fourier transform of f (t), and hence determine f˜(ω) to within a constant. Use this result to solve for h(t) the integral equation  ∞ 2 e−t(t−2x)/2 h(t) dt = e3x /8 . −∞

As a standard result,

 F f (t) = iωf˜(ω),

187

Integral equations

though we will not need this relationship in the following solution. From its definition,  ∞ 1 F [ tf (t) ] = √ tf (t) e−iωt dt 2π −∞    ∞ 1 d f˜ 1 d −iωt . f (t) e dt = i = √ −i dω dω 2π −∞ Now, for the particular given function,  ∞ 1 2 f˜(ω) = √ e−t /2 e−iωt dt 2π −∞ ∞  2  ∞ −t 2 /2 −iωt 1 1 te e e−t /2 e−iωt +√ =√ dt −iω −iω 2π 2π −∞ −∞ =0−

1 d f˜ i . iω dω

Hence, d f˜ 2 = −ωf˜ ⇒ ln f˜ = − 12 ω2 + k ⇒ f˜ = Ae−ω /2 , dω ˜ giving f (ω) to within a multiplicative constant. Now, we are also given  ∞ 2 e−t(t−2x)/2 h(t) dt = e3x /8 ,  ∞ −∞ 2 2 2 e−(t−x) /2 ex /2 h(t) dt = e3x /8 , ⇒ −∞  ∞ 2 2 e−(x−t) /2 h(t) dt = e−x /8 . ⇒

(∗)

(∗∗)

−∞

The LHS of (∗∗) is a convolution integral, and so applying the convolution theorem for Fourier transforms and result (∗), used twice, yields " # √ 2 2 2 ˜ 2π Ae−ω /2 h(ω) = F e−(x/2) /2 = Ae−(2ω) /2 , √ √ 2 2 ˜ 2π h(ω) = e−3ω /2 = e−( 3ω) /2 , ⇒ √ 2 1 1 2 ⇒ h(t) = √ e−(t/ 3) /2 = √ e−t /6 . 2π A 2π A We now substitute in (∗∗) to determine A:  ∞ 1 2 2 2 e−t /6 dt = e−x /8 , e−(x−t) /2 √ 2π A −∞  ∞ 1 2 2 2 e−2t /3 ext e−x /2 ex /8 dt = 1, √ 2π A −∞      ∞ 3x 2 2 1 t− exp − dt = 1. √ 3 4 2π A −∞

188

Integral equations

From the normalization of the Gaussian integral, this implies that 1 2 =√ √ , √ 2π A 2π 3 which in turn means A =



3/2, giving finally that ' h(t) =

2 −t 2 /6 . e 3π

13.11 At an international “peace” conference a large number of delegates are seated around a circular table with each delegation sitting near its allies and diametrically opposite the delegation most bitterly opposed to it. The position of a delegate is denoted by θ , with 0 ≤ θ ≤ 2π. The fury f (θ ) felt by the delegate at θ is the sum of his own natural hostility h(θ ) and the influences on him of each of the other delegates; a delegate at position φ contributes an amount K(θ − φ)f (φ). Thus  2π K(θ − φ)f (φ) dφ. f (θ ) = h(θ ) + 0

Show that if K(ψ) takes the form K(ψ) = k0 + k1 cos ψ then f (θ ) = h(θ ) + p + q cos θ + r sin θ and evaluate p, q and r. A positive value for k1 implies that delegates tend to placate their opponents but upset their allies, whilst negative values imply that they calm their allies but infuriate their opponents. A walkout will occur if f (θ ) exceeds a certain threshold value for some θ . Is this more likely to happen for positive or for negative values of k1 ?

Given that K(ψ) = k0 + k1 cos ψ, we try a solution f (θ) = h(θ) + p + q cos θ + r sin θ, reducing the equation to p + q cos θ + r sin θ  2π = [k0 + k1 (cos θ cos φ + sin θ sin φ)] 0

× [h(φ) + p + q cos φ + r sin φ] dφ = k0 (H + 2πp) + k1 (Hc cos θ + Hs sin θ + πq cos θ + πr sin θ),  2π  2π  2π where H = 0 h(z) dz, Hc = 0 h(z) cos z dz and Hs = 0 h(z) sin z dz. Thus, on equating the constant terms and the coefficients of cos θ and sin θ, we have p = k0 H + 2πk0 p



q = k1 Hc + k1 πq



r = k1 Hs + k1 πr



k0 H , 1 − 2πk0 k1 Hc , q= 1 − k1 π k1 Hs . r= 1 − k1 π p=

189

Integral equations

And so the full solution for f (θ) is given by k0 H k 1 Hs k1 Hc cos θ + sin θ + 1 − 2πk0 1 − k1 π 1 − k1 π 1/2 k0 H k1  2 = h(θ) + + cos(θ − α), Hc + Hs2 1 − 2πk0 1 − k1 π

f (θ) = h(θ) +

where tan α = Hs /Hc . Clearly, the maximum value of f (θ) will depend upon h(θ) and its various integrals, but it is most likely to exceed any particular value if k1 is positive and ≈ π −1 . Stick with your friends! 13.13 The operator M is defined by

 Mf (x) ≡



K(x, y)f (y) dy, −∞

where K(x, y) = 1 inside the square |x| < a, |y| < a and K(x, y) = 0 elsewhere. Consider the possible eigenvalues of M and the eigenfunctions that correspond to them; show that the only possible eigenvalues are 0 and 2a and determine the corresponding eigenfunctions. Hence find the general solution of  ∞ K(x, y)f (y) dy. f (x) = g(x) + λ −∞

From the given properties of K(x, y) we can assert the following. (i) No matter what the form of f (x),  a Mf (x) = 0 if |x| > a. (ii) All functions for which both −a f (y) dy = 0 and f (x) = 0 for |x| > a are eigenfunctions corresponding to eigenvalue 0.  a (iii) For any function f (x), the integral −a f (y) dy is equal to a constant whose value is independent of x; thus f (x) can only be an eigenfunction if it is equal to a constant, μ, for a −a ≤ x ≤ a and is zero otherwise. For this case −a f (y) dy = 2aμ and the eigenvalue is 2a. Point (iii) gives the only possible non-zero eigenvalue, whilst point (ii) shows that eigenfunctions corresponding to zero eigenvalues do exist. Denote by S(x, a) the function that has unit value for |x| ≤ a and zero value otherwise; K(x, y) could be expressed as K(x, y) = S(x, a)S(y, a). Substitute the trial solution f (x) = g(x) + kS(x, a) into  ∞ K(x, y)f (y) dy. f (x) = g(x) + λ −∞

This gives  g(x) + kS(x, a) = g(x) + λ kS(x, a) = λS(x, a)



 −∞ a −a

K(x, y)[ g(y) + kS(y, a) ] dy,

g(y) dy + λk 2aS(x, a).

190

Integral equations

Here, having replaced K(x, y) by S(x, a)S(y, a), we use the factor S(y, a) to reduce the limits of the y-integration from ±∞ to ±a. As this result is to hold for all x we must have 

λG k= , 1 − 2aλ

where G =

a

g(y) dy. −a

The general solution is thus

f (x) =

⎧ ⎨

g(x) +

⎩ g(x)

λG 1 − 2aλ

for |x| ≤ a, for |x| > a.

13.15 Use Fredholm theory to show that, for the kernel K(x, z) = (x + z) exp(x − z) over the interval [0, 1], the resolvent kernel is    exp(x − z) (x + z) − λ 12 x + 12 z − xz − 13 R(x, z; λ) = , 1 2 1 − λ − 12 λ and hence solve



1

y(x) = x + 2 2

(x + z) exp(x − z) y(z) dz,

0

expressing your answer in terms of In , where In =

1 0

un exp(−u) du.

We calculate successive values of dn and Dn (x, z) using the Fredholm recurrence relations:  dn =

b

Dn−1 (x, x) dx,  b K(x, z1 )Dn−1 (z1 , z) dz1 , Dn (x, z) = K(x, z)dn − n a

a

starting from d0 = 1 and D0 (x, z) = (x + z)ex−z . In the first iteration we obtain  d1 =

1

(u + u)eu−u du = 1, 0  1 x−z (x + u)ex−u (u + z)eu−z du D1 (x, z) = (x + z)e (1) − 1 0  1 [xz + (x + z)u + u2 ] du = (x + z)ex−z − ex−z 0  = ex−z 12 (x + z) − xz − 13 .

191

Integral equations

Performing the second iteration gives  1   d2 = eu−u u − u2 − 13 du = 12 − 13 − 13 = − 16 , 0   D2 (x, z) = (x + z)ex−z − 16  1  (x + u)ex−u eu−z 12 (u + z) − uz − 13 du −2   %0   = ex−z − 16 (x + z) − 2 x 14 + 2z − 2z − 13 + 16 + % &  x z = 0. − 12 = ex−z − 16 (x + z) − 2 − 12

z 4



z 3



1 6

 &

Since D2 (x, z) = 0, d3 = 0, D3 (x, z) = 0, etc. Consequently both D(x, z; λ) and d(λ) are finite, rather than infinite, series:  D(x, z; λ) = (x + z)ex−z − λ 12 (x + z) − xz − 13 ex−z ,   λ2 1 2 λ. d(λ) = 1 − λ + − 16 = 1 − λ − 12 2! The resolvent kernel R(x, z; λ), given by the ratio D(x, z; λ)/d(λ), is therefore as stated in the question. For the particular integral equation, λ = 2 and f (x) = x 2 . It follows that   4 = − 43 and D(x, z : λ) = 2xz + 23 ex−z . d(λ) = 1 − 2 − 12 The solution is therefore given by



1

y(x) = f (x) + λ

R(x, z; λ)f (z) dz 0



1

=x +2 2

0



1

=x − 2

  2xz + 23 z2 ex−z − 43

(3xz3 + z2 )ex−z dz

0

= x 2 − (3xI3 + I2 )ex .

dz

14

Complex variables

14.1 Find an analytic function of z = x + iy whose imaginary part is (y cos y + x sin y) exp x.

If the required function is f (z) = u + iv, with v = (y cos y + x sin y) exp x, then, from the Cauchy–Riemann equations, ∂u ∂v = ex (y cos y + x sin y + sin y) = − . ∂x ∂y Integrating with respect to y gives  u = −ex (y cos y + x sin y + sin y) dy + f (x)    = −ex y sin y − sin y dy − x cos y − cos y + f (x) = −ex (y sin y + cos y − x cos y − cos y) + f (x) = ex (x cos y − y sin y) + f (x). We determine f (x) by applying the second Cauchy–Riemann equation, which equates ∂u/∂x with ∂v/∂y:

By comparison,

∂u = ex (x cos y − y sin y + cos y) + f (x), ∂x ∂v = ex (cos y − y sin y + x cos y). ∂y f (x) = 0 ⇒ f (x) = k,

where k is a real constant that can be taken as zero. Hence, the analytic function is given by f (z) = u + iv = ex (x cos y − y sin y + iy cos y + ix sin y) = ex [ (cos y + i sin y)(x + iy) ] = ex eiy (x + iy) = zez . The final line confirms explicitly that this is a function of z alone (as opposed to a function of both z and z∗ ). 192

193

Complex variables

14.3 Find the radii of convergence of the following Taylor series: ∞ ∞   zn n!zn , (b) , ln n nn n=2 n=1 2 ∞ ∞    n+p n n zn nln n , (d) z , with p real. (c) n n=1 n=1

(a)

In each case we consider the series as

 n

an zn and apply the formula

1 = lim |an |1/n R n→∞ derived from considering the Cauchy root test for absolute convergence. (a)

  1 1/n 1 = 1, since − n−1 ln ln n → 0 as n → ∞. = lim R n→∞ ln n

Thus R = 1. For interest, we also note that at the point z = 1 the series is ∞ ∞   1 1 > , ln n n n=2 n=2

which diverges. This shows that the given series diverges at this point on its circle of convergence. (b)

 1/n n! 1 . = lim R n→∞ nn

Since the nth root of n! tends to n as n → ∞, the limit of this ratio is that of n/n, namely unity. Thus R = 1 and the series converges inside the unit circle. (c)

 1/n 1 = lim n(ln n)/n = lim nln n n→∞ n→∞ R   ln n = lim exp ln n = exp(0) = 1. n→∞ n

Thus R = 1 and the series converges inside the unit circle. It is obvious that the series diverges at the point z = 1. (d)

  2 1/n  n+p n n+p n = lim n→∞ n n   p n = lim 1 + = ep . n→∞ n

1 = lim n→∞ R



Thus R = e−p and the series converges inside a circle of this radius centered on the origin z = 0.

194

Complex variables

14.5 Determine the types of singularities (if any) possessed by the following functions at z = 0 and z = ∞: (a) (z − 2)−1 , (b) (1 + z3 )/z2 , (c) sinh(1/z), (e) z1/2 /(1 + z2 )1/2 . (d) ez /z3 ,

(a) Although (z − 2)−1 has a simple pole at z = 2, at both z = 0 and z = ∞ it is well behaved and analytic. b) Near z = 0, f (z) = (1 + z3 )/z2 behaves like 1/z2 and so has a double pole there. It is clear that as z → ∞ f (z) behaves as z and so has a simple pole there; this can be made more formal by setting z = 1/ξ to obtain g(ξ ) = ξ 2 + ξ −1 and considering ξ → 0. This leads to the same conclusion. (c) As z → ∞, f (z) = sinh(1/z) behaves like sinh ξ as ξ → 0, i.e. analytically. However, the definition of the sinh function involves an infinite series – in this case an infinite series of inverse powers of z. Thus, no finite n for which lim [ zn f (z) ] is finite

z→0

can be found, and f (z) has an essential singularity at z = 0. (d) Near z = 0, f (z) = ez /z3 behaves as 1/z3 and has a pole of order 3 at the origin. At z = ∞ it has an obvious essential singularity; formally, the series expansion of e1/ξ about ξ = 0 contains arbitrarily high inverse powers of ξ . (e) Near z = 0, f (z) = z1/2 /(1 + z2 )1/2 behaves as z1/2 and therefore has a branch point there. To investigate its behavior as z → ∞, we set z = 1/ξ and obtain 1/2  1/2  ξ ξ −1 = ∼ ξ 1/2 as ξ → 0. f (z) = g(ξ ) = 1 + ξ −2 ξ2 + 1 Hence f (z) also has a branch point at z = ∞. 14.7 Find the real and imaginary parts of the functions (i) z2 , (ii) ez , and (iii) cosh πz. By considering the values taken by these parts on the boundaries of the region x ≥ 0, y ≤ 1, determine the solution of Laplace’s equation in that region that satisfies the boundary conditions φ(x, 0) = 0,

φ(0, y) = 0,

φ(x, 1) = x,

φ(1, y) = y + sin πy.

Writing fk (z) = uk (x, y) + ivk (x, y), we have (i) (ii) (iii)

f1 (z) f2 (z) f3 (z)

=

z2 = (x + iy)2



u1 = x 2 − y 2 and v1 = 2xy,

=

ez = ex+iy = ex (cos y + i sin y)



u2 = ex cos y and v2 = ex sin y,

=

cosh πz = cosh πx cos πy + i sinh πx sin πy



u3 = cosh πx cos πy and v3 = sinh πx sin πy.

All of these u and v are necessarily solutions of Laplace’s equation (this follows from the Cauchy–Riemann equations), and, since Laplace’s equation is linear, we can form

195

Complex variables

any linear combination of them and it will also be a solution. We need to choose the combination that matches the given boundary conditions. Since the third and fourth conditions involve x and sin πy, and these appear only in v1 and v3 , respectively, let us try a linear combination of them: φ(x, y) = A(2xy) + B(sinh πx sin πy). The requirement φ(x, 0) = 0 is clearly satisfied, as is φ(0, y) = 0. The condition φ(x, 1) = x becomes 2Ax + 0 = x, requiring A = 12 , and the remaining condition, φ(1, y) = y + sin πy, takes the form y + B sinh π sin πy = y + sin πy, thus determining B as 1/ sinh π. With φ a solution of Laplace’s equation and all of the boundary conditions satisfied, the uniqueness theorem guarantees that φ(x, y) = xy +

sinh πx sin πy sinh π

is the correct solution. 14.9 The fundamental theorem of algebra states that, for a complex polynomial pn (z) of degree n, the equation pn (z) = 0 has precisely n complex roots. By applying Liouville’s theorem, which reads If f (z) is analytic and bounded for all z then f is a constant, to f (z) = 1/pn (z), prove that pn (z) = 0 has at least one complex root. Factor out that root to obtain pn−1 (z) and, by repeating the process, prove the fundamental theorem.

We prove this result by the method of contradiction. Suppose pn (z) = 0 has no roots in the complex plane, then fn (z) = 1/pn (z) is bounded for all z and, by Liouville’s theorem, is therefore a constant. It follows that pn (z) is also a constant and that n = 0. However, if n > 0 we have a contradiction and it was wrong to suppose that pn (z) = 0 has no roots; it must have at least one. Let one of them be z = z1 ; i.e. pn (z), being a polynomial, can be written pn (z) = (z − z1 )pn−1 (z). Now, by considering fn−1 (z) = 1/pn−1 (z) in just the same way, we can conclude that either n − 1 = 0 or a further reduction is possible. It is clear that n such reductions are needed to make f0 a constant, thus establishing that pn (z) = 0 has precisely n (complex) roots. 14.11 The function f (z) = (1 − z2 )1/2 of the complex variable z is defined to be real and positive on the real axis for −1 < x < 1. Using cuts running along the real axis for 1 < x < +∞ and −∞ < x < −1, show how f (z) is made single-valued and evaluate it on the upper and lower sides of both cuts. Use these results and a suitable contour in the complex z-plane to evaluate the integral  ∞ dx I= . x(x 2 − 1)1/2 1 Confirm your answer by making the substitution x = sec θ .

196

Complex variables

As usual when dealing with branch cuts aimed at making a multi-valued function into a single-valued one, we introduce polar coordinates centered on the branch points. For f (z) the branch points are at z = ±1, and so we define r1 as the distance of z from the point 1 and θ1 as the angle the line joining 1 to z makes with the part of the x-axis for which 1 < x < +∞, with 0 ≤ θ1 ≤ 2π. Similarly, r2 and θ2 are centered on the point −1, but θ2 lies in the range −π ≤ θ2 ≤ π. With these definitions, f (z) = (1 − z2 )1/2 = (1 − z)1/2 (1 + z)1/2  1/2 = (−r1 eiθ1 )(r2 eiθ2 ) = (r1 r2 )1/2 ei(θ1 +θ2 −π)/2 . In the final line the choice between exp(+iπ) and exp(−iπ) for dealing with the minus sign appearing before r1 in the second line was resolved by the requirement that f (z) is real and positive when −1 < x < 1 with y = 0. For these values of z, r1 = 1 − x, r2 = 1 + x, θ1 = π and θ2 = 0. Thus, f (z) = [ (1 − x)(1 + x) ]1/2 e(π+0−π)/2 = (1 − x 2 )1/2 ei0 = +(1 − x 2 )1/2 , as required. Now applying the same prescription to points lying just above and just below each of the cuts, we have r1 = x − 1 r2 = x + 1 θ1 = 0

x > 1, y = 0+ ⇒ x > 1, y = 0−

f (z) = (x 2 − 1)1/2 ei(0+0−π)/2 = −i(x 2 − 1)1/2 , r1 = x − 1 r2 = x + 1 θ1 = 2π

⇒ x < −1, y = 0+



r2 = −x − 1

θ1 = π

θ2 = π

f (z) = (x 2 − 1)1/2 ei(π+π−π)/2 = i(x 2 − 1)1/2 , r1 = 1 − x

x < −1, y = 0−

θ2 = 0

f (z) = (x 2 − 1)1/2 ei(2π+0−π)/2 = i(x 2 − 1)1/2 , r1 = 1 − x



θ2 = 0

r2 = −x − 1

θ1 = π

θ2 = −π

f (z) = (x 2 − 1)1/2 ei(π−π−π)/2 = −i(x 2 − 1)1/2 .

To use these results to evaluate the given integral I , consider the contour integral   dz dz . J = = 2 )1/2 z(1 − z zf (z) C c Here C is a large circle (consisting of arcs 1 and 2 in the upper and lower half-planes, respectively) of radius R centered on the origin but indented along the positive and negative x-axes by the cuts considered earlier. At the ends of the cuts are two small circles γ1 and γ2 that enclose the branch points z = 1 and z = −1, respectively. Thus the complete closed contour, starting from γ1 and moving along the positive real axis, consists of, in order, circle γ1 , cut C1 , arc 1 , cut C2 , circle γ2 , cut C3 , arc 2 and cut C4 , leading back to γ1 .

197

Complex variables

On the arcs 1 and 2 the integrand is O(R −2 ) and the contributions to the contour integral → 0 as R → ∞. For the small circle γ1 , where we can set z = 1 + ρeiφ with dz = iρeiφ dφ, we have  γ1

dz = z(1 + z)1/2 (1 − z)1/2





(1 +

0

ρeiφ )(2

iρeiφ dφ, + ρeiφ )1/2 (−ρeiφ )1/2

and this → 0 as ρ → 0. Similarly, the small circle γ2 contributes nothing to the contour integral. This leaves only the contributions from the four arms of the branch cuts. To relate these to I we use our previous results about the value of f (z) on the various arms: 



on C1 , z = x and

= C1

1

 on C2 , z = −x and

 =

C2

 on C3 , z = −x and

C3

1



 =  =

C1

dx = iI ; x[ −i(x 2 − 1)1/2 ]

−dx = iI ; −x[ i(x 2 − 1)1/2 ]



−dx = iI ; −x[ −i(x 2 − 1)1/2 ]

1

dx = iI. − 1)1/2 ]

1

 on C4 , z = x and





x[ i(x 2

So the full contour integral around C has the value 4iI . But, this must be the same as 2πi times the residue of z−1 (1 − z2 )−1/2 at z = 0, which is the only pole of the integrand inside the contour. The residue is clearly unity, and so we deduce that I = π/2. This particular integral can be evaluated much more simply using elementary methods. Setting x = sec θ with dx = sec θ tan θ dθ gives 



dx 2 − 1)1/2 x(x 1  π/2  π/2 π sec θ tan θ dθ = = dθ = , 2 1/2 sec θ (sec θ − 1) 2 0 0

I =

and so verifies the result obtained by contour integration. 14.13 The following is an alternative (and roundabout!) way of evaluating the Gaussian integral. (a) Prove that the integral of [exp(iπz2 )]cosecπz around the parallelogram with corners ±1/2 ± R exp(iπ/4) has the value 2i. (b) Show that the parts of the contour parallel to the real axis give no contribution when R → ∞. (c) Evaluate the integrals along the other two sides by putting z = r exp(iπ/4) and working in terms of z + 12 and z − 12 . Hence by letting R → ∞ show that  ∞ 2 e−π r dr = 1. −∞

198

Complex variables

Im z

L2

L1

− 12

1 2

R π/4

Re z

R

Figure 14.1 The parallelogram contour used in Problem 14.13.

The integral is 



2

eiπz cosec πz dz = C

C

2

eiπz dz sin πz

and the suggested contour C is shown in Figure 14.1. (a) The integrand has (simple) poles only on the real axis at z = n, where n is an integer. The only such pole enclosed by C is at z = 0. The residue there is 2

a−1

1 zeiπz = lim = . z→0 sin πz π

The value of the integral around C is therefore 2πi × (π −1 ) = 2i. (b) On the parts of C parallel to the real axis, z = ±Reiπ/4 + x , where − 12 ≤ x ≤ 12 . The integrand is thus given by "  2 # 1 exp iπ ± Reiπ/4 + x sin πz "  # 1 2 = exp iπ R 2 eiπ/2 ± 2Rx eiπ/4 + x sin πz   2πiRx 1 2 2 exp −πR ± √ (1 + i) + iπx = sin πz 2   √ 2 = O exp[−πR ∓ 2πRx ]

f (z) =

→ 0 as R → ∞. Since the integration range is finite (− 12 ≤ x ≤ 12 ), the integrals → 0 as R → ∞.

199

Complex variables

(c) On the first of the other two sides, let us set z = 12 + reiπ/4 with −R ≤ r ≤ R. The corresponding integral I1 is  2 I1 = eiπz cosec πz dz L1 "   #  R exp iπ 1 + reiπ/4 2 2  eiπ/4 dr  1 = iπ/4 −R sin π 2 + re  R iπ/4 e exp(iπreiπ/4 ) exp(iπr 2 i)eiπ/4 = dr cos(πreiπ/4 ) −R  R 2 i exp(iπreiπ/4 )e−πr dr. = cos(πreiπ/4 ) −R Similarly (remembering the sense of integration), the remaining side contributes  R 2 i exp(−iπreiπ/4 )e−πr dr. I2 = − − cos(πreiπ/4 ) −R Adding together all four contributions gives  R 2 i[ exp(iπreiπ/4 ) + exp(−iπreiπ/4 ) ]e−πr 0+0+ dr, cos(πreiπ/4 ) −R which simplifies to



R

2ie−πr dr. 2

−R

From part (a), this must be equal to 2i as R → ∞, and so





−∞

e−πr dr = 1. 2

15

Applications of complex variables

Many of the problems in this chapter involve contour integration and the choice of a suitable contour. In order to save the space taken by drawing several broadly similar contours that differ only in notation, the positions of poles, the values of lengths or angles, or other minor details, we make reference to Figure 15.1 which shows a number of typical contour types.

15.1 In the method of complex impedances for a.c. circuits, an inductance L is represented by a complex impedance ZL = iωL and a capacitance C by ZC = 1/(iωC). Kirchhoff’s circuit laws,    Ii = 0 at a node and Zi I i = Vj around any closed loop, i

i

j

are then applied as if the circuit were a d.c. one. Apply this method to the a.c. bridge connected as in Figure 15.2 to show that if the resistance R is chosen as R = (L/C)1/2 then the amplitude of the current IR through it is independent of the angular frequency ω of the applied a.c. voltage V0 eiωt . Determine how the phase of IR , relative to that of the voltage source, varies with the angular frequency ω.

Omitting the common factor eiωt from all currents and voltages, let the current drawn from the voltage source be (the complex quantity) I and the current flowing from A to D be I1 . Then the currents in the remaining branches are AE : I − I1 , DB : I1 − IR and + IR . EB : I − I1  Applying i Zi Ii = j Vj to three separate loops yields

loop ADBA loop ADEA loop DBED

200

1 (I1 − IR ) = V0 , iωC 1 iωL I1 + R IR − (I − I1 ) = 0, iωC iωL I1 +

1 (I1 − IR ) − iωL (I − I1 + IR ) − R IR = 0. iωC

201

Applications of complex variables

B Γ

α

O

B

Γ

A

R A

O

(a)

O

(b)

( c)

Γ

Γ R

O

R

O

−R

Γ

γ+

γ−

−R

Γ

R

(d)

γ

γ1

O

γ2

( e)

(f)

Γ

Γ

Γ L

L O

O

γ1

γ

γ2

O

λ

λ (g)

(h)

(i)

Figure 15.1 Typical contours for use in contour integration.

A C

L

V0 ei ω t ~

IR

D

E

R L

C B

Figure 15.2 The inductor–capacitor–resistor network for Problem 15.1.

L

202

Applications of complex variables

Now, denoting (LC)−1 by ω02 and choosing R as (L/C)1/2 = (ω0 C)−1 , we can write these equations as follows:   ω2 1 − 2 I1 − IR = iωCV0 , ω0  2 ω ω IR = 0, −I + 1 − 2 I1 + i ω0 ω0     ω2 ω2 ω2 ω IR = 0. I + 1 − 2 I1 + −1 + 2 − i ω0 ω02 ω0 ω0 Eliminating I from the last two of these yields       ω2 ω2 iω ω2 1 − 2 I1 − 1+ 2 +1 1 − 2 IR = 0. ω0 ω0 ω0 ω0 Thus, ω2 ω02 ω02 + ω2 ω02 (iωCV0 + IR ) IR = I = . 1 ω ω0 (ω0 + iω) ω02 − ω2 1+i ω0 1+

After some cancellation and rearrangement,   2 ω0 − ω2 IR = ω0 (ω0 − iω)(iωCV0 + IR ), (iωω0 − ω2 ) IR = ω0 ω(iω0 + ω)CV0 , and so IR = ω0 CV0

iω0 + ω (iω0 + ω) (−iω0 − ω) = ω0 CV0 iω0 − ω (iω0 − ω)(−iω0 − ω) ω2 − ω2 − 2iωω0 . = ω0 CV0 0 ω02 + ω2

From this we can read off " #1/2 2 ω2 − ω02 + 4ω2 ω02 = ω0 CV0 , i.e. independent of ω, |IR | = ω0 CV0 ω02 + ω2 and φ = phase of IR = tan−1

−2ωω0 . ω02 − ω2

Thus IR (which was arbitrarily and notionally defined as flowing from D to E in the equivalent d.c. circuit) has an imaginary part that is always negative but a real part that changes sign as ω passes through ω0 . Its phase φ, relative to that of the voltage source, therefore varies from 0 when ω is small to −π when ω is large.

203

Applications of complex variables

15.3 For the function

 z+c , f (z) = ln z−c 

where c is real, show that the real part u of f is constant on a circle of radius c cosech u centered on the point z = c coth u. Use this result to show that the electrical capacitance per unit length of two parallel cylinders of radii a, placed with their axes 2d apart, is proportional to [cosh−1 (d/a)]−1 .

From

 f (z) = ln

z+c z−c



    z + c  + i arg z + c , = ln  z − c z−c

we have that

   z + c  1 (x + c)2 + y 2  = ln  u = ln  z − c  2 (x − c)2 + y 2



e2u =

(x + c)2 + y 2 . (x − c)2 + y 2

The curve upon which u(x, y) is constant is therefore given by (x 2 − 2cx + c2 + y 2 )e2u = x 2 + 2xc + c2 + y 2 . This can be rewritten as x 2 (e2u − 1) − 2xc(e2u + 1) + y 2 (e2u − 1) + c2 (e2u − 1) = 0, e2u + 1 + y 2 + c2 = 0, x 2 − 2xc 2u e −1 x 2 − 2xc coth u + y 2 + c2 = 0, which, in conic-section form, becomes (x − c coth u)2 + y 2 = c2 coth2 u − c2 = c2 cosech2 u. This is a circle with center (c coth u, 0) and radius |c cosech u|. Now consider two such circles with the same value of |c cosech u|, equal to a, but different values of u satisfying c coth u1 = −d and c coth u2 = +d. These two equations imply that u1 = −u2 , corresponding physically to equal but opposite charges −Q and +Q placed on identical cylindrical conductors that coincide with the circles; the conductors are raised to potentials u1 and u2 . We have already established that we need c coth u2 = d and c cosech u2 = a. Dividing these two equations gives cosh u2 = d/a. The capacitance (per unit length) of the arrangement is given by the magnitude of the charge on one conductor divided by the potential difference between the conductors that results from the presence of that charge, i.e. C= as stated in the question.

Q 1 1 ∝ = , −1 u 2 − u1 2u2 2 cosh (d/a)

204

Applications of complex variables

15.5 By considering in turn the transformations z = 12 c(w + w −1 )

and w = exp ζ,

where z = x + iy, w = r exp iθ , ζ = ξ + iη and c is a real positive constant, show that z = c cosh ζ maps the strip ξ ≥ 0, 0 ≤ η ≤ 2π, onto the whole z-plane. Which curves in the z-plane correspond to the lines ξ = constant and η = constant? Identify those corresponding to ξ = 0, η = 0 and η = 2π. The electric potential φ of a charged conducting strip −c ≤ x ≤ c, y = 0, satisfies φ ∼ −k ln(x 2 + y 2 )1/2 for large values of (x 2 + y 2 )1/2 , with φ constant on the strip. Show that φ = Re [−k cosh−1 (z/c)] and that the magnitude of the electric field near the strip is k(c2 − x 2 )−1/2 .

We first note that the combined transformation is given by c ζ (e + e−ζ ) = c cosh ζ 2

z=

z ζ = cosh−1 . c



The successive connections linking the strip in the ζ -plane and its image in the z-plane are z = c cosh ζ = c cosh(ξ + iη) = c cosh ξ cos η + ic sinh ξ sin η, with ξ > 0, 0 ≤ η ≤ 2π, reiθ = w = eζ = eξ eiη , with the strip as 1 < r < ∞, 0 ≤ θ ≤ 2π, c (w + w−1 ) 2 c = [ r(cos θ + i sin θ) + r −1 (cos θ − i sin θ) ] 2    1 c 1 c r+ cos θ + i r− sin θ. = 2 r 2 r

x + iy = z =

This last expression for z and the previous specification of the strip in terms of r and θ show that both x and y can take all values, i.e. that the original strip in the ζ -plane is mapped onto the whole of the z-plane. From the two expressions for z we also see that x = c cosh ξ cos η and y = c sinh ξ sin η. For ξ constant, the contour in the xy-plane, obtained by eliminating η, is y2 x2 + = 1, c2 cosh2 ξ c2 sinh2 ξ

i.e. an ellipse.

The eccentricity of the ellipse is given by  e=

c2 cosh2 ξ − c2 sinh2 ξ c2 cosh2 ξ

1/2 =

1 . cosh ξ

The foci of the ellipse are at ± e× the major semi-axis, i.e. ±1/ cosh ξ × c cosh ξ = ±c. This is independent of ξ and so all the ellipses are confocal.

205

Applications of complex variables

Similarly, for η constant, the contour is x2 y2 − = 1. c2 cos2 η c2 sin2 η This is one of a set of confocal hyperbolae. (i) ξ = 0 ⇒ y = 0, x = c cos η. This is the finite line (degenerate ellipse) on the x-axis, −c ≤ x ≤ c. (ii) η = 0 ⇒ y = 0, x = c cosh ξ . This is a part of the x-axis not covered in (i), c < x < ∞. The other part, −∞ < x < −c, corresponds to η = π. (iii) This is the same as (the first case) in (ii). Now, in the ζ -plane, consider the real part of the function F (ζ ) = −kζ , with k real. On ξ = 0 [ case (i) above ] it reduces to Re {−ikη}, which is zero for all η, i.e. a constant. This implies that the real part of the transformed function will be a constant (actually zero) on −c ≤ x ≤ c in the z-plane. Further, (x 2 + y 2 )1/2 = (c2 cosh2 ξ cos2 η + c2 sinh2 ξ sin2 η)1/2 ≈ 12 ceξ for large ξ , ⇒

ξ ≈ ln(x 2 + y 2 )1/2 + fixed constant.

Hence, Re {−kζ } = −kξ ≈ −k ln(x 2 + y 2 )1/2 for large (x 2 + y 2 )1/2 . Thus, the transformation z c produces a function in the z-plane that satisfies the stated boundary conditions (as well as satisfying Laplace’s equation). It is therefore the required solution. The electric field near the conducting strip, where y = 0 and z2 = x 2 , can have no component in the x-direction (except at the points x = ±c), but its magnitude is still given by     k k  = . E = | f (z) | =  − √  2 2 2 (c − x 2 )1/2 z −c F (ζ ) = −kζ



f (z) = −k cosh−1

15.7 Prove that if f (z) has a simple zero at z0 then 1/f (z) has residue 1/f (z0 ) there. Hence evaluate  π sin θ dθ, a − sin θ −π where a is real and > 1.

If f (z) is analytic and has a simple zero at z = z0 then it can be written as f (z) =

∞  n=1

an (z − z0 )n ,

with a1 = 0.

206

Applications of complex variables

Using a binomial expansion, 1 = f (z)

 a1 (z − z0 ) 1 +

1 ∞  n=2

an (z − z0 )n−1 a1



1 (1 + b1 (z − z0 ) + b2 (z − z0 )2 + · · · ), = a1 (z − z0 ) for some coefficients, bi . The residue at z = z0 is clearly a1−1 . But, from differentiating the Taylor expansion, f (z) =

∞ 

nan (z − z0 )n−1 ,

n=1





f (z0 ) = a1 + 0 + 0 + · · · = a1 ,

1 1 . can also be expressed as a1 f (z0 ) Denote the required integral by I and consider the contour integral   dz 2iz dz J = = , 2 1 −1 C C 2aiz − z + 1 a − (z − z ) 2i

i.e. the residue =

where C is the unit circle, i.e. √ 15.1 with R = 1. The denominator has √ contour (c) of Figure 2 simple zeros √ at z = ai ± −a + 1 = i(a ± a 2 − 1). Since a is strictly√greater than 1, α = i(a − a 2 − 1) lies strictly inside the unit circle, whilst β = i(a + a 2 − 1) lies strictly outside it (and need not be considered further). Extending the previous result to the case of h(z) = g(z)/f (z), where g(z) is analytic at z0 , the residue of h(z) at z = z0 can be seen to be g(z0 )/f (z0 ). Applying this, we find that the residue of the integrand at z = α is given by    2iz  α iα   =√ . = √  2ai − 2z  ai − ai + i a 2 − 1 a2 − 1 z=α Now on the unit circle, z = eiθ with dz = i eiθ dθ, and J can be written as  π  π i eiθ dθ i(cos θ + i sin θ) dθ = . J = 1 a − sin θ iθ −iθ −π −π a − (e − e ) 2i Hence, √ i(a − a 2 − 1) I = −Re J = −Re 2πi √ a2 − 1   a = 2π √ −1 . a2 − 1

207

Applications of complex variables

Although it is not asked for, we can also deduce from the fact that the residue at z = α is purely imaginary that  π cos θ dθ = 0, −π a − sin θ a result that can also be obtained by more elementary means, when it is noted that the numerator of the integrand is the derivative of the denominator. 15.9 Prove that





4x 4

0

 cos mx π  −m/2 − e−m 4e dx = 2 + 5x + 1 6

for m > 0.

Since, when z is on the real axis, the integrand is equal to Re

(z2

eimz eimz = Re , 2 + 1)(4z + 1) (z + i)(z − i)(2z + i)(2z − i)

we consider the integral of f (z) =

eimz around contour (d) in (z + i)(z − i)(2z + i)(2z − i)

Figure 15.1. As |f (z)| ∼ |z|−4 as z → ∞ and m > 0, all the conditions for Jordan’s lemma to hold are satisfied and the integral around the large semi-circle contributes nothing. For this integrand there are two poles inside the contour, at z = i and at z = 12 i. The respective residues are ie−m e−m = 2i 3i i 6

and

e−m/2 −2ie−m/2 . = 3i 3 (− 2i ) 2i 2

The residue theorem therefore reads  −m   ∞ ie 2ie−m/2 eimx dx + 0 = 2πi − , 4 2 6 3 −∞ 4x + 5x + 1 and the stated result follows from equating real parts and changing the lower integration limit, recognizing that the integrand is symmetric about x = 0 and so the integral from 0 to ∞ is equal to half of that from −∞ to ∞. 15.11 Using a suitable cut plane, prove that if α is real and 0 < α < 1 then  ∞ −α x dx 1 +x 0 has the value π cosec πα.

z−α is not single1+z valued. We therefore need to perform the contour integration in a cut plane; contour (f) of Figure 15.1 is a suitable contour. We will be making use of the fact that, because the As α is not an integer, the complex form of the integrand f (z) =

208

Applications of complex variables

integrand takes different values on γ1 and γ2 , the contributions coming from these two parts of the complete contour, although related, do not cancel. The contributions from γ and  are both zero because: z z−α (i) around γ , |zf (z)| ∼ = z1−α → 0 as |z| → 0, since α < 1; 1 z z−α = z−α → 0 as |z| → ∞, since α > 0. (ii) around , |zf (z)| ∼ z Therefore, the only contributions come from the cut; on γ1 , z = xe0i , whilst on γ2 , z = xe2πi . The only pole inside the contour is a simple one at z = −1 = eiπ , where the residue is e−iπα . The residue theorem now reads  ∞ −α  ∞ −α −2πiα x x e dx = 2πi e−iπα , 0+ dx + 0 − 1+x 1 + xe2πi 0 0  ∞ −α x −2πiα dx = 2πi e−iπα . ⇒ (1 − e ) 1+x 0 This can be rearranged to read  ∞ −α 2πi e−iπα 2πi x π dx = = iπα , = −2πiα −iπα 1+x (1 − e ) e −e sin πα 0 thus establishing the stated result. 15.13 By integrating a suitable function around a large semi-circle in the upper half plane and a small semi-circle centered on the origin, determine the value of  ∞ (ln x)2 I= dx 1 + x2 0 and deduce, as a by-product of your calculation, that  ∞ ln x dx = 0. 1 + x2 0

The suggested contour is that shown in Figure 15.1(e), but with only one indentation γ on the real axis (at z = 0) and with R = ∞. The appropriate complex function is f (z) =

(ln z)2 . 1 + z2

The only pole inside the contour is at z = i, and the residue there is given by (ln 1 + i(π/2))2 π2 (ln i)2 = =− . i+i 2i 8i To evaluate the integral around γ , we set z = ρ eiθ with ln z = ln ρ + iθ and dz = iρ eiθ dθ; the integral becomes  0 2 ln ρ + 2iθ ln ρ − θ 2 iρ eiθ dθ, which → 0 as ρ → 0. 1 + ρ 2 e2iθ π

209

Applications of complex variables

Thus γ contributes nothing. Even more obviously, on , |zf (z)| ∼ z−1 and tends to zero as |z| → ∞, showing that  also contributes nothing. On γ+ , z = xei0 and the contribution is equal to I . On γ− , z = xeiπ and the contribution is (remembering that the contour actually runs from x = ∞ to x = 0) given by 



(ln x + iπ)2 iπ e dx 1 + x2 0  ∞  ∞ ln x 1 2 = I + 2iπ dx − π dx. 2 1 + x 1 + x2 0 0

I− = −

The residue theorem for the complete closed contour thus reads 



0 + I + 0 + I + 2iπ 0

 ∞ ln x dx − π 2 tan−1 x 0 = 2πi 2 1+x



−π 2 8i

 .

Equating the real parts ⇒ 2I − 12 π 3 = − 14 π 3 ⇒ I = 18 π 3 . Equating the imaginary parts gives the stated by-product. 15.15 Prove that ∞  −∞

1 n2

+

3 n 4

+

1 8

= 4π.

Carry out the summation numerically, say between −4 and 4, and note how much of the sum comes from values near the poles of the contour integration.

In order to evaluate this sum, we must first find a function of z that takes the value of the corresponding term in the sum whenever z is an integer. Clearly this is 1 z2 +

3 z 4

+

1 8

.

Further, to make use of the properties of contour integrals, we need to multiply this function by one that has simple poles at the same points, each with unit residue. An appropriate choice of integrand is therefore f (z) =

π cot πz π cot πz  . = 3 1 + 4z + 8 z + 12 z + 14

z2

The contour to be used must enclose all integer values of z, both positive and negative and, in practical terms, must give zero contribution for |z| → ∞, except possibly on the real axis. A large circle C, centered on the origin (see contour (c) in Figure 15.1) suggests itself.

210

Applications of complex variables

As |zf (z)| → 0 on C, the contour integral has value zero. This implies that the residues at the enclosed poles add up to zero. The residues are   π cot − 12 π − 12 + 14   π cot − 14 π

=0

at z = − 12 ,

= −4π at z = − 14 , − 14 + 12 ∞  1    at z = n, −∞ < n < ∞. 1 n + 2 n + 14 n=−∞ The quoted result follows immediately. For the rough numerical summation we tabulate n, D(n) = n2 + 34 n + term of the series, 1/D(n): n

D(n)

1/D(n)

−4 −3 −2 −1 0 1 2 3 4

13.125 6.875 2.625 0.375 0.125 1.875 5.625 11.375 19.125

0.076 0.146 0.381 2.667 8.000 0.533 0.178 0.088 0.052

1 8

and the nth

The total of these nine terms is 12.121; this is to be compared with the total for the entire infinite series (of positive terms), which is 4π = 12.566. It will be seen that the sum is dominated by the terms for n = 0 and n = −1. These two values bracket the positions on the real axis of the poles at z = − 12 and z = − 14 . 15.17 By considering the integral of 

sin αz αz

2

π , sin πz

α
0). When the integration line is made part of a closed contour C, the inversion integral becomes  f (t) = C

e−s est − est + sest ds. s2

For t < 0, all the terms → 0 as Re s → ∞, and so we close the contour in the right half-plane, as in contour (h) of Figure 15.1. On , s times the integrand → 0, and, as

212

Applications of complex variables

the contour encloses no poles, it follows that the integral along L is zero. Thus f (t) = 0 for t < 0. For t > 1, all terms → 0 as Re s → −∞, and so we close the contour in the left half-plane, as in contour (g) of Figure 15.1. On , s times the integrand again → 0, and, as this contour also encloses no poles, it again follows that the integral along L is zero. Thus f (t) = 0 for t > 1, as well as for t < 0. For 0 < t < 1, we need to separate the Bromwich integral into two parts (guided by the different ways in which the parts behave as |s| → ∞):  −s st  e e (s − 1)est f (t) = ds + ds ≡ I1 + I2 . s2 s2 L L For I1 the exponent is s(t − 1); t − 1 is negative and so, as in the case t < 0, we close the contour in the right half-plane [ contour (h) ]. No poles are included in this contour, and we conclude that I1 = 0. For I2 the exponent is st, indicating that (g) is the appropriate contour. However, (s − 1)/s 2 does have a pole at s = 0 and that is inside the contour. The integral around  contributes nothing (that is why it was chosen), and the integral along L must be equal to the residue of (s − 1)est /s 2 at s = 0. Now,    1 1 s2t 2 (s − 1)est 1 1 − + · · · = − 2 + (1 − t) + · · · . 1 + st + = s2 s s2 2! s s The residue, and hence the value of I2 , is therefore 1 − t. Since I1 has been shown to have value 0, 1 − t is also the expression for f (t) for 0 < t < 1. 15.21 Use contour (i) in Figure 15.1 to show that the function with Laplace transform s −1/2 is (πx)−1/2 . [For an integrand of the form r −1/2 exp(−rx), change variable to t = r 1/2 .]

With the suggested contour no poles of s −1/2 esx are enclosed and so the integral of (2πi)−1 s −1/2 esx around the closed curve must have the value zero. It is also clear that the integral along  will be zero since Re s < 0 on . For the small circle γ enclosing the origin, set s = ρ eiθ , with ds = iρ eiθ dθ, and consider  2π lim ρ −1/2 e−iθ/2 exp(xρ eiθ )iρ eiθ dθ. ρ→0 0

This → 0 as ρ → 0 (as ρ 1/2 ). On the upper cut, γ1 , s = reiπ and the contribution to the integral is  0 −iπ/2 e 1 exp(rxeiπ )eiπ dr, 2πi ∞ r 1/2 whilst, on the lower cut, γ2 , s = re−iπ , and its contribution to the integral is  ∞ iπ/2 1 e exp(rxe−iπ )e−iπ dr. 2πi 0 r 1/2

213

Applications of complex variables

Combining the two (and making both integrals run over the same range) gives  ∞  1 1 ∞ 1 −t 2 x 2i −rx − e dr = − 2t dt, after setting r = t 2 , e 2πi 0 r 1/2 π 0 t √ 2 π =− √ . π2 x Since this must add to the Bromwich integral along L to make zero, it follows that the function with Laplace transform s −1/2 is (πx)−1/2 .

16

Probability

16.1 By shading or numbering Venn diagrams, determine which of the following are valid relationships between events. For those that are, prove the relationship using de Morgan’s laws. (a) (b) (c) (d) (e)

(X¯ ∪ Y ) = X ∩ Y¯ . X¯ ∪ Y¯ = (X ∪ Y ). (X ∪ Y ) ∩ Z = (X ∪ Z) ∩ Y . ¯ X ∪ (Y ∩ Z) = (X ∪ Y¯ ) ∩ Z. ¯ X ∪ (Y ∩ Z) = (X ∪ Y¯ ) ∪ Z.

For each part of this question we refer to the corresponding part of Figure 16.1. (a) This relationship is correct as both expressions define the shaded region that is both inside X and outside Y . (b) This relationship is not valid. The LHS specifies the whole sample space apart from the region marked with the heavy shading. The RHS defines the region that is lightly shaded. The unmarked regions of X and Y are included in the former but not in the latter. (c) This relationship is not valid. The LHS specifies the sum of the regions marked 2, 3 and 4 in the figure, whilst the RHS defines the sum of the regions marked 1, 3 and 4. (d) This relationship is not valid. On the LHS, Y ∩ Z is the whole sample space apart from regions 3 and 4. So X ∪ (Y ∩ Z) consists of all regions except for region 3. On the RHS, X ∪ Y¯ contains all regions except 3 and 7. The events Z¯ contain regions 1, 6, 7 and 8 and so (X ∪ Y¯ ) ∩ Z¯ consists of regions 1, 6 and 8. Thus regions 2, 4, 5 and 7 are in one specification but not in the other. (e) This relationship is valid. The LHS is as found in (d), namely all regions except for region 3. The RHS consists of the union (as opposed to the intersection) of the two subregions found in (d) and thus contains those regions found in either or both of X ∪ Y¯ (1, 2, 4, 5, 6 and 8) and Z¯ (1, 6, 7 and 8). This covers all regions except region 3 – in agreement with those found for the LHS. For the two valid relationships, their proofs using de Morgan’s laws are:

(a) (e)

(X¯ ∪ Y ) = X¯ ∩ Y¯ = X ∩ Y¯ , ¯ = (X ∪ Y¯ ) ∪ Z. ¯ X ∪ (Y ∩ Z) = X ∪ (Y¯ ∪ Z)

Here we have also used the result that the complement of the complement of a set is the set itself. 214

215

Probability

X

Y

X

Y

(a) X

(b) Y

1 2 4 3

X

Z

Z

Y

6 1 2 43 5

7 8

(d) and (e)

(c)

Figure 16.1 The Venn diagrams used in Problem 16.1.

16.3 A and B each have two unbiased four-faced dice, the four faces being numbered 1, 2, 3 and 4. Without looking, B tries to guess the sum x of the numbers on the bottom faces of A’s two dice after they have been thrown onto a table. If the guess is correct B receives x 2 euros, but if not he loses x euros. Determine B’s expected gain per throw of A’s dice when he adopts each of the following strategies: (a) he selects x at random in the range 2 ≤ x ≤ 8; (b) he throws his own two dice and guesses x to be whatever they indicate; (c) he takes your advice and always chooses the same value for x. Which number would you advise?

We first calculate the probabilities p(x) and the corresponding gains g(x) = p(x)x 2 − [1 − p(x)]x for each value of the total x. Expressing both in units of 1/16, they are as follows: x p(x) g(x)

2

3

4

5

6

7

8

1 −26

2 −24

3 −4

4 40

3 30

2 0

1 −56

(a) If B’s guess is random in the range 2 ≤ x ≤ 8 then his expected return is 1 1 40 (−26 − 24 − 4 + 40 + 30 + 0 − 56) = − = −0.36 euros. 16 7 112

216

Probability

(b) If he picks by throwing his own dice then his distribution of guesses is the same as that of p(x) and his expected return is 1 1 [1(−26) + 2(−24) + 3(−4) + 4(40) + 3(30) + 2(0) + 1(−56)] 16 16 108 = 0.42 euros. = 256 (c) If B chooses y, then his expected return is h(y) = p(y)y 2 −



p(x)x.

x=y

An additional line in the table (in the same units) would read h(x), −74, −56, −20, 40, 46, 32, −8. You should not advise B, but take his place, guess “6” each time, and expect an average profit of 46/16 = 2.87 euros per throw. 16.5 Two duelists, A and B, take alternate shots at each other, and the duel is over when a shot (fatal or otherwise!) hits its target. Each shot fired by A has a probability α of hitting B, and each shot fired by B has a probability β of hitting A. Calculate the probabilities P1 and P2 , defined as follows, that A will win such a duel: P1 , A fires the first shot; P2 , B fires the first shot. If they agree to fire simultaneously, rather than alternately, what is the probability P3 that A will win, i.e. hit B without being hit himself?

Each shot has only two possible outcomes, a hit or a miss. P1 is the probability that A will win when it is his turn to fire the next shot, and he is still able to do so (event W ). There are three possible outcomes of the first two shots: C1 , A hits with his shot; C2 , A misses but B hits; C3 , both miss. Thus  P1 = Pr(Ci ) Pr(W |Ci ) i



= [α × 1] + [(1 − α)β × 0] + [(1 − α)(1 − β) × P1 ] α P1 = . α + β − αβ

When B fires first but misses, the situation is the one just considered. But if B hits with his first shot then clearly A’s chances of winning are zero. Since these are the only two possible outcomes of B’s first shot, we can write P2 = [β × 0] + [(1 − β) × P1 ]



P2 =

(1 − β)α . α + β − αβ

When both fire at the same time there are four possible outcomes Di to the first round: D1 , A hits and B misses; D2 , B hits but A misses; D3 , they both hit; D4 , they both miss. If getting hit, even if you manage to hit your opponent, does not count as a win, then  Pr(Di ) Pr(W |Di ) P3 = i

= [α(1 − β) × 1] + [(1 − α)β × 0] + [αβ × 0] + [(1 − α)(1 − β) × P3 ].

217

Probability

This can be rearranged as P3 =

α(1 − β) = P2 . α + β − αβ

Thus the result is the same as if B had fired first. However, we also note that if all that matters to A is that B is hit, whether or not he is hit himself, then the third bracket takes the value αβ × 1 and P3 takes the same value as P1 . 16.7 An electronics assembly firm buys its microchips from three different suppliers; half of them are bought from firm X, whilst firms Y and Z supply 30% and 20%, respectively. The suppliers use different quality-control procedures and the percentages of defective chips are 2%, 4% and 4% for X, Y and Z, respectively. The probabilities that a defective chip will fail two or more assembly-line tests are 40%, 60% and 80%, respectively, whilst all defective chips have a 10% chance of escaping detection. An assembler finds a chip that fails only one test. What is the probability that it came from supplier X?

Since the number of tests failed by a defective chip are mutually exclusive outcomes (0, 1 or ≥ 2), a chip supplied by X has a probability of failing just one test given by 0.02(1 − 0.1 − 0.4) = 0.010. The corresponding probabilities for chips supplied by Y and Z are 0.04(1 − 0.1 − 0.6) = 0.012 and 0.04(1 − 0.1 − 0.8) = 0.004, respectively. Using “1” to denote failing a single test, Bayes’ theorem gives the probability that the chip was supplied by X as Pr(1|X) Pr(X) Pr(1|X) Pr(X) + Pr(1|Y ) Pr(Y ) + Pr(1|Z) Pr(Z) 50 0.010 × 0.5 = . = 0.010 × 0.5 + 0.012 × 0.3 + 0.004 × 0.2 94

Pr(X|1) =

16.9 A boy is selected at random from amongst the children belonging to families with n children. It is known that he has at least two sisters. Show that the probability that he has k − 1 brothers is (n − 1)! , (2n−1 − n)(k − 1)!(n − k)! for 1 ≤ k ≤ n − 2 and zero for other values of k. Assume that boys and girls are equally likely.

The boy has n − 1 siblings. Let Aj be the event that j − 1 of them are brothers, i.e. his family contains j boys and n − j girls. The probability of event Aj is n−1

Pr(Aj ) =  n

Cj −1

 1 n−1 2

n−1 C j −1 j =1

 1 n−1 = 2

(n − 1)! . 2n−1 (j − 1)!(n − j )!

If B is the event that the boy has at least two sisters, then  1 1 ≤ j ≤ n − 2, Pr(B|Aj ) = 0 n − 1 ≤ j ≤ n.

218

Probability

Now we apply Bayes’ theorem to give the probability that he has k − 1 brothers: 1 Pr(Ak ) Pr(Ak |B) = n−2 , j =1 1 Pr(Aj ) for 1 ≤ k ≤ n − 2. The denominator of this expression is the sum 1 = ( 12 + 12 )n−1 =  n−1 n n−1 Cj −1 12 , but omitting the j = n − 1 and the j = n terms, and so is equal j =1 to 1−

(n − 1)! (n − 1)! 1  − n−1 = n−1 2n−1 − (n − 1) − 1 . (n − 2)! 1! 2 (n − 1)! 0! 2

2n−1

Thus, Pr(Ak |B) =

(n − 1)! 2n−1 (n − 1)! = n−1 , n−1 n−1 2 (k − 1)!(n − k)! 2 −n (2 − n)(k − 1)!(n − k)!

as given in the question. 16.11 A set of 2N + 1 rods consists of one of each integer length 1, 2, . . . , 2N, 2N + 1. Three, of lengths a, b and c, are selected, of which a is the longest. By considering the possible values of b and c, determine the number of ways in which a non-degenerate triangle (i.e. one of non-zero area) can be formed (i) if a is even, and (ii) if a is odd. Combine these results appropriately to determine the total number of non-degenerate triangles that can be formed using three of the 2N + 1 rods, and hence show that the probability that such a triangle can be formed from a random selection (without replacement) of three rods is (N − 1)(4N + 1) . 2(4N 2 − 1)

Rod a is the longest of the three rods. As no two are the same length, let a > b > c. To form a non-degenerate triangle we require that b + c > a, and, in consequence, 4 ≤ a ≤ 2N + 1. (i) With a even. Consider each b (< a) in turn and determine how many values of c allow a triangle to be made: b

Values of c

a − 1 2, 3, · · · , a − 2 a − 2 3, 4, · · · , a − 3 ··· ··· 1 1 a + 1 a 2 2

Number of c values a−3 a−5 ··· 1

Thus, there are 1 + 3 + 5 + · · · + (a − 3) possible triangles when a is even. (ii) A table for odd a is similar, except that the last line will read b = 12 (a + 3), c = 12 (a − 1) or 12 (a + 1), and the number of c values = 2. Thus there are 2 + 4 + 6 + · · · + (a − 3) possible triangles when a is odd.

219

Probability

To find the total number n(N) of possible triangles, we group together the cases a = 2m and a = 2m + 1, where m = 1, 2, . . . , N. Then, n(N) =

N 

[1 + 3 + · · · + (2m − 3)] + [2 + 4 + · · · + (2m + 1 − 3)]

m=2

= =

N 2m−2  

k=

m=2 k=1  2 16 N(N

N 

1 (2m 2

− 2)(2m − 1) =

N m=2

2m2 − 3m + 1

m=2

 + 1)(2N + 1) − 1 − 3 12 N(N + 1) − 1 + N − 1

N [2(N + 1)(2N + 1) − 9(N + 1) + 6] 6 N N = (4N 2 − 3N − 1) = (4N + 1)(N − 1). 6 6 The number of ways that three rods can be drawn at random (without replacement) is (2N + 1)(2N)(2N − 1)/3! and so the probability that they can form a triangle is =

3! (N − 1)(4N + 1) N(4N + 1)(N − 1) = , 6 (2N + 1)(2N)(2N − 1) 2(4N 2 − 1) as stated in the question. 16.13 The duration (in minutes) of a telephone call made from a public call-box is a random variable T . The probability density function of T is ⎧ t < 0, ⎨ 0 1 f (t) = 0 ≤ t < 1, ⎩ 2−2t ke t ≥ 1, where k is a constant. To pay for the call, 20 pence has to be inserted at the beginning, and a further 20 pence after each subsequent half-minute. Determine by how much the average cost of a call exceeds the cost of a call of average length charged at 40 pence per minute.

From the normalization of the PDF, we must have  ∞  ∞ 1 1 ke−2 1= f (t) dt = + ke−2t dt = + 2 2 2 0 1



k = e2 .

The average length of a call is given by  ∞  1 1 t dt + t e2 e−2t dt t¯ = 2 0 1  2 −2t ∞  ∞ 2 −2t  ∞ 3 1 te e 1 1 e2 e−2t e e 11 + = + = 1. + dt = + + = 22 −2 1 2 4 2 2 −2 1 4 4 1 Let pn = Pr{ 12 (n − 1) < t < 12 n}. The corresponding cost is cn = 20n. Clearly, p1 = p2 = 14 and, for n > 2,  −2t n/2  n/2 1 2 −2t 2 e pn = e e dt = e = e2 (e − 1)e−n . −2 (n−1)/2 2 (n−1)/2

220

Probability

The average cost of a call is therefore   ∞ ∞  1 1  1 2 −n c¯ = 20 n e (e − 1)e ne−n . = 15 + 10e2 (e − 1) +2 + 4 4 n=3 2 n=3 Now, the final summation might be recognized as part of an arithmetico-geometric series whose sum can be found from the standard formula rd a + S= , 1−r (1 − r)2 with a = 0, d = 1 and r = e−1 , or could be evaluated directly by noting that as a geometric series, ∞ 

e−nx =

n=0

1 . 1 − e−x

Differentiating this with respect to x and then setting x = 1 gives −

∞ 

ne−nx = −

n=0

e−x (1 − e−x )2



∞  n=0

ne−n =

e−1 . (1 − e−1 )2

From either method it follows that ∞  e ne−n = − e−1 − 2e−2 2 (e − 1) n=3 =

e − e + 2 − e−1 − 2 + 4e−1 − 2e−2 3e−1 − 2e−2 = . (e − 1)2 (e − 1)2

The total charge therefore exceeds that of a call of average length (1 minute) charged at 40 pence per minute by the amount (in pence) 15 + 10e2 (e − 1)

5e + 5 3e−1 − 2e−2 10(3e − 2) − 25e + 25 = = 10.82. − 40 = 2 (e − 1) e−1 e−1

16.15 A tennis tournament is arranged on a straight knockout basis for 2n players, and for each round, except the final, opponents for those still in the competition are drawn at random. The quality of the field is so even that in any match it is equally likely that either player will win. Two of the players have surnames that begin with “Q”. Find the probabilities that they play each other (a) in the final, (b) at some stage in the tournament.

Let pr be the probability that before the rth round the two players are both still in the tournament (and, by implication, have not met each other). Clearly, p1 = 1. Before the rth round there are 2n+1−r players left in. For both “Q” players to still be in before the (r + 1)th round, Q1 must avoid Q2 in the draw and both must win their matches. Thus   2n+1−r − 2 1 2 pr . pr+1 = n+1−r 2 −1 2

221

Probability

(a) The probability that they meet in the final is pn , given by 2n − 2 1 2n−1 − 2 1 22 − 2 1 pn = 1 n · · · 2 − 1 4 2n−1 − 1 4 22 − 1 4  n−1  n−1  (2 1 − 1)(2n−2 − 1) · · · (21 − 1) 2n−1 = 4 (2n − 1)(2n−1 − 1) · · · (22 − 1)  n−1 1 1 2n−1 n = 4 2 −1 1 = n−1 n . 2 (2 − 1) (b) The more general solution to the recurrence relation derived above is 2n − 2 1 2n−1 − 2 1 2n+2−r − 2 1 · · · pr = 1 n 2 − 1 4 2n−1 − 1 4 2n+2−r − 1 4   n−1  r−1 − 1)(2n−2 − 1) · · · (2n+1−r − 1) 1 r−1 (2 2 = 4 (2n − 1)(2n−1 − 1) · · · (2n+2−r − 1)  r−1 n+1−r 1 2 −1 = . 2 2n − 1 Before the rth round, if they are both still in the tournament, the probability that they will be drawn against each other is (2n−r+1 − 1)−1 . Consequently, the chance that they will meet at some stage is n  r−1 n+1−r  1 2 −1 1 pr n−r+1 = n−1 n−r+1 − 1 2 − 1 2 2 2 r=1 r=1 n   1  1 r−1 = n 2 − 1 r=1 2

n 

1

=

1 1 − ( 12 )n 1 = n−1 . 1 n 2 −1 1− 2 2

This same conclusion can also be reached in the following way. The probability that Q1 is not put out of (i.e. wins) the tournament is ( 12 )n . It follows that the probability that Q1 is put out is 1 − ( 12 )n and that the player responsible is Q2 with probability [1 − ( 12 )n ]/(2n − 1) = 2−n . Similarly, the probability that Q2 is put out and that the player responsible is Q1 is also 2−n . These are exclusive events but cover all cases in which Q1 and Q2 meet during the tournament, the probability of which is therefore 2 × 2−n = 21−n .

222

Probability

16.17 This problem is about interrelated binomial trials. (a) In two sets of binomial trials T and t, the probabilities that a trial has a successful outcome are P and p, respectively, with corresponding probabilities of failure of Q = 1 − P and q = 1 − p. One “game” consists of a trial T , followed, if T is successful, by a trial t and then a further trial T . The two trials continue to alternate until one of the T -trials fails, at which point the game ends. The score S for the game is the total number of successes in the t-trials. Find the PGF for S and use it to show that Pp Pp(1 − P q) E[S] = . , V [S] = Q Q2 (b) Two normal unbiased six-faced dice A and B are rolled alternately starting with A; if A shows a 6 the experiment ends. If B shows an odd number no points are scored, one point is scored for a 2 or a 4, and two points are awarded for a 6. Find the average and standard deviation of the score for the experiment and show that the latter is the greater.

(a) This is a situation in which the score for the game is a variable-length sum, the length N being determined by the outcome of the T -trials. The probability that N = n is given by hn = P n Q, since n T -trials must succeed and then be followed by a failing T -trial. Thus the PGF for the length of each “game” is given by χN (t) ≡

∞ 

hn t =

n=0

n

∞ 

P n Qt n =

n=0

Q . 1 − Pt

= 0 with probability For each permitted Bernoulli t-trial, Xi = 1 with probability p and Xi q; its PGF is thus X (t) = q + pt. The score for the game is S = N i=1 Xi and its PGF is given by the compound function S (t)

= χN (X (t)) Q , = 1 − P (q + pt)

in which the PGF for a single t-trial forms the argument of the PGF for the length of each “game”. It follows that the mean of S is found from QPp QPp Pp ⇒ E[S] = S (1) = = . S (t) = 2 2 (1 − P q − Ppt) (1 − P ) Q To calculate the variance of S we need to find S (t)

=

2QP 2 p 2 (1 − P q − Ppt)3

S (1).



This second derivative is S (1)

=

2P 2 p 2 . Q2

The variance is therefore − [ S (1)]2 2P p Pp P 2 p 2 − = + Q2 Q Q2 Pp(Pp + Q) Pp(P − P q + Q) Pp(1 − P q) = = = . 2 2 Q Q Q2

V [S] =

S (1) + 2 2

S (1)

223

Probability

(b) For die A: P =

5 6

and Q =

1 6

giving χN (t) = 1/(6 − 5t).

For die B: Pr(X = 0) = 36 , Pr(X = 1) = t 2 )/6. The PGF for the game score S is thus =

S (t)

2 6

and Pr(X = 2) =

1 6−

5 (3 6

+ 2t +

t 2)

We need to evaluate the first two derivatives of

giving X (t) = (3 + 2t +

6 . 21 − 10t − 5t 2

S (t)

at t = 1, as follows:

−6(−10 − 10t) 60 + 60t = (21 − 10t − 5t 2 )2 (21 − 10t − 5t 2 )2 120 10 = = 3.33, S (1) = 62 3 60 2(60 + 60t)(−10 − 10t) − S (t) = 2 2 (21 − 10t − 5t ) (21 − 10t − 5t 2 )3 60 2(120)(−20) 215 = − . S (1) = 3 36 (6) 9 S (t)



=

1 6

E[S] =



=

Substituting the calculated values gives V [S] as  2 145 10 215 10 = + − , V [S] = 9 3 3 9 from which it follows that σS =

 V [S] = 4.01, i.e. greater than the mean.

16.19 A point P is chosen at random on the circle x 2 + y 2 = 1. The random variable X denotes the distance of P from (1, 0). Find the mean and variance of X and the probability that X is greater than its mean.

With O as the center of the unit circle and Q as the point (1, 0), let OP make an angle θ with the x-axis OQ. The random variable X then has the value 2 sin(θ/2) with θ uniformly distributed on (0, 2π), i.e. f (x) dx =

1 dθ. 2π

The mean of X is given straightforwardly by      2π  2 θ 4 1 1 θ 2π Xf (x) dx = 2 sin = . dθ = −2 cos X = 2 2π π 2 0 π 0 0 For the variance we have σX2





= X  − X = 2

2

  1 16 16 4 1 16 θ dθ − 2 = 2π − 2 = 2 − 2 . 4 sin 2 2π π 2π 2 π π 2

0

224

Probability

When X = X = 4/π, the angle θ = 2 sin−1 (2/π) and so Pr(X > X) =

2π − 4 sin−1 2π

2 π = 0.561.

16.21 The number of errors needing correction on each page of a set of proofs follows a Poisson distribution of mean μ. The cost of the first correction on any page is α and that of each subsequent correction on the same page is β. Prove that the average cost of correcting a page is α + β(μ − 1) − (α − β)e−μ .

Since the number of errors on a page is Poisson distributed, the probability of n errors on any particular page is Pr(n errors) = pn = e−μ

μn . n!

The average cost per page, found by averaging the corresponding cost over all values of n, is c = 0 p0 + αp1 +

∞  [α + (n − 1)β]pn n=2

= αμe−μ + (α − β)

∞  n=2

pn + β

∞ 

npn .

n=2

 ∞ Now, ∞ n=0 pn = 1 and, for a Poisson distribution, n=0 npn = μ. These can be used to evaluate the above, once the n = 0 and n = 1 terms have been removed. Thus c = αμe−μ + (α − β)(1 − e−μ − μe−μ ) + β(μ − 0 − μe−μ ) = α + β(μ − 1) + e−μ (αμ − α + β − μα + μβ − μβ) = α + β(μ − 1) + e−μ (β − α), as given in the question. 16.23 The probability distribution for the number of eggs in a clutch is Po(λ), and the probability that each egg will hatch is p (independently of the size of the clutch). Show by direct calculation that the probability distribution for the number of chicks that hatch is Po(λp).

Clearly, to determine the probability that a clutch produces k chicks, we must consider clutches of size n, for all n ≥ k, and for each such clutch find the probability that exactly k of the n chicks do hatch. We then average over all n, weighting the results according to the distribution of n. The probability that k chicks hatch from a clutch of size n is n Ck p k q n−k , where q = 1 − p. The probability that the clutch is of size n is e−λ λn /n!. Consequently, the

225

Probability

overall probability of k chicks hatching from a clutch is Pr(k chicks) =

∞ 

e−λ

n=k

λn n!

= e−λ p k λk = e−λ

n

Ck p k q n−k

∞  (λq)n−k

n=k ∞ k 

(λp) k!

n!

n! , k! (n − k)!

set n − k = m,

(λq)m m! m=0

(λp)k λq e k! e−λp (λp)k , = k! = e−λ

since q = 1 − p. Thus Pr(k chicks) is distributed as a Poisson distribution with parameter μ = λp. 16.25 Under EU legislation on harmonization, all kippers are to weigh 0.2000 kg and vendors who sell underweight kippers must be fined by their government. The weight of a kipper is normally distributed with a mean of 0.2000 kg and a standard deviation of 0.0100 kg. They are packed in cartons of 100 and large quantities of them are sold. Every day a carton is to be selected at random from each vendor and tested according to one of the following schemes, which have been approved for the purpose. (a) The entire carton is weighed and the vendor is fined 2500 euros if the average weight of a kipper is less than 0.1975 kg. (b) Twenty five kippers are selected at random from the carton; the vendor is fined 100 euros if the average weight of a kipper is less than 0.1980 kg. (c) Kippers are removed one at a time, at random, until one has been found that weighs more than 0.2000 kg; the vendor is fined 4n(n − 1) euros, where n is the number of kippers removed. Which scheme should the Chancellor of the Exchequer be urging his government to adopt?

For these calculations we measure weights in grammes. (a) For this scheme we √ have a normal distribution with mean μ = 200 and s.d. σ = 10. The s.d. for a carton is 100 σ = 100 and the mean weight is 20 000. There is a penalty if the weight of a carton is less than 19 750. This critical value represents a standard variable of Z=

19 750 − 20 000 = −2.5. 100

The probability that Z < −2.5 = 1 − (2.5) = 1 − 0.9938 = 0.0062. Thus the average fine per carton tested on this scheme is 0.0062 × 2500 = 15.5 euros. (b) For this scheme the general parameters are the same but the mean weight of the √ sample measured is 5000 and its s.d. is 25 (10) = 50. The Z-value at which a fine is

226

Probability

imposed is Z=

(198 × 25) − 5000 = −1. 50

The probability that Z < −1.0 = 1 − (1.0) = 1 − 0.8413 = 0.1587. Thus the average fine per carton tested on this scheme is 0.1587 × 100 = 15.9 euros. (c) This scheme is a series of Bernoulli trials in which the probability of success is 1 (since half of all kippers weigh more than 200 and the distribution is normal). The 2 probability that it will take n kippers to find one that passes the test is q n−1 p = ( 12 )n . The expected fine is therefore    n 2 14 1 4n(n − 1) = 4  3 = 16 euros. f = 1 2 n=2 ∞ 

2

The expression for the sum was found by twice differentiating the sum of the geometric  series r n with respect to r, as follows: ∞  n=0

rn =

1 1−r



∞ 

nr n−1 =

n=1



∞ 

1 (1 − r)2

n(n − 1)r n−2 =

n=2



∞ 

n(n − 1)r n =

n=2

2 (1 − r)3

2r 2 . (1 − r)3

There is, in fact, little to choose between the schemes on monetary grounds; no doubt political considerations, such as the current unemployment rate, will decide! 16.27 A practical-class demonstrator sends his 12 students to the storeroom to collect apparatus for an experiment, but forgets to tell each which type of component to bring. There are three types, A, B and C, held in the stores (in large numbers) in the proportions 20%, 30% and 50%, respectively, and each student picks a component at random. In order to set up one experiment, one unit each of A and B and two units of C are needed. Let Pr(N ) be the probability that at least N experiments can be set up. (a) Evaluate Pr(3). (b) Find an expression for Pr(N ) in terms of k1 and k2 , the numbers of components of types A and B, respectively, selected by the students. Show that Pr(2) can be written in the form Pr(2) = (0.5)12

6  i=2

12

Ci (0.4)i

8−i 

12−i

Cj (0.6)j .

j =2

(c) By considering the conditions under which no experiments can be set up, show that Pr(1) = 0.9145.

227

Probability

(a) To make three experiments possible the 12 components picked must be three each of A and B and six of C. The probability of this is given by the multinomial distribution as Pr(3) =

(12)! (0.2)3 (0.3)3 (0.5)6 = 0.06237. 3! 3! 6!

(b) Let the numbers of A, B and C selected be k1 , k2 and k3 , respectively, and consider when at least N experiments can be set up. We have the obvious inequalities k1 ≥ N, k2 ≥ N and k3 ≥ 2N. In addition k3 = 12 − k1 − k2 , implying that k2 ≤ 12 − 2N − k1 . Further, k1 cannot be greater than 12 − 3N if at least N experiments are to be set up, as each requires three other components that are not of type A. These inequalities set the limits on the acceptable values of k1 and k2 (k3 is not a third independent variable). Thus Pr(N) is given by 12−3N  12−2N−k  1 k1 ≥N

k2 ≥N

(12)! (0.2)k1 (0.3)k2 (0.5)12−k1 −k2 . k1 ! k2 ! (12 − k1 − k2 )!

The answer to part (a) is a particular case of this with N = 3, when each summation reduces to a single term. For N = 2 the expression becomes Pr(2) =

6 8−k  1 k1 ≥2

(12)! (0.2)k1 (0.3)k2 (0.5)12−k1 −k2 k ! k ! (12 − k − k )! 1 2 k ≥2 1 2 2

= (0.5)12 = (0.5)

12

6  8−i  (12)! (0.2/0.5)i (12 − i)! (0.3/0.5)j i! (12 − i)! j ! (12 − i − j )! i=2 j =2 6 

12

Ci (0.4)

i

8−i 

12−i

Cj (0.6)j .

j =2

i=2

(c) No experiment can be set up if any one of the following four events occurs: A1 = (k1 = 0), A2 = (k2 = 0), A3 = (k3 = 0) and A4 = (k3 = 1). The probability for the union of these four events is given by Pr(A1 ∪ A2 ∪ A3 ∪ A4 ) =

4 

Pr(Ai ) −

i=1



Pr(Ai ∩ Aj ) + · · · .

i,j

The probabilities Pr(Ai ) are straightforward to calculate as follows: Pr(A1 ) = (1 − 0.2)12 ,

Pr(A2 ) = (1 − 0.3)12 ,

Pr(A3 ) = (1 − 0.5)12 ,

Pr(A4 ) =

12

C1 (1 − 0.5)12 (0.5).

The calculation of the probability for the intersection of two events is typified by Pr(A1 ∩ A2 ) = [1 − (0.2 + 0.3)]12 and Pr(A1 ∩ A4 ) =

12

C1 [1 − (0.2 + 0.5)]11 (0.5)1 .

228

Probability

A few trial evaluations show that these are of order 10−4 and can be ignored by comparison with the larger terms in the first sum, which are (after rounding) 4 

Pr(Ai ) = (0.8)12 + (0.7)12 + (0.5)12 + 12(0.5)11 (0.5)

i=1

= 0.0687 + 0.0138 + 0.0002 + 0.0029 = 0.0856. Since the probability of no experiments being possible is 0.0856, it follows that Pr(1) = 0.9144. 16.29 The continuous random variables X and Y have a joint PDF proportional to xy(x − y)2 with 0 ≤ x ≤ 1 and 0 ≤ y ≤ 1. Find the marginal distributions for X and Y and show that they are negatively correlated with correlation coefficient − 23 .

This PDF is clearly symmetric between x and y. We start by finding its normalization constant c:    1 1 11 11 c 11 3 2 2 3 −2 + = . c(x y − 2x y + xy ) dx dy = c 42 33 24 36 0 0 Thus, we must have that c = 36. The marginal distribution for x is given by  1 (x 3 y − 2x 2 y 2 + xy 3 ) dy f (x) = 36 0   = 36 12 x 3 − 23 x 2 + 14 x = 18x 3 − 24x 2 + 9x, and the mean of x by 

1

μX = x¯ =

(18x 4 − 24x 3 + 9x 2 ) dx =

0

3 18 24 9 − + = . 5 4 3 5

By symmetry, the marginal distribution and the mean for y are 18y 3 − 24y 2 + 9y and 35 , respectively. To calculate the correlation coefficient we also need the variances of x and y and their covariance. The variances, obviously equal, are given by  1  2 x 2 (18x 3 − 24x 2 + 9x) dx − 35 σX2 = 0

9 18 24 9 − + − = 6 5 4 25 900 − 1440 + 675 − 108 9 = = . 300 100 The standard deviations σX and σY are therefore both equal to 3/10.

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Probability

The covariance is calculated next; it is given by Cov [X, Y ] = XY  − μX μY  1 1 33 = 36 (x 4 y 2 − 2x 3 y 3 + x 2 y 4 ) dx dy − 55 0 0 36 72 36 9 = − + − 5 × 3 4 × 4 3 × 5 25 12 9 12 9 = − + − 5 2 5 25 3 120 − 225 + 120 − 18 =− . = 50 50 Finally, Corr [X, Y ] =

−3 2 Cov [X, Y ] = 3 503 = − . σX σY 3 10 10

16.31 Two continuous random variables X and Y have a joint probability distribution f (x, y) = A(x 2 + y 2 ), where A is a constant and 0 ≤ x ≤ a, 0 ≤ y ≤ a. Show that X and Y are negatively correlated with correlation coefficient −15/73. By sketching a rough contour map of f (x, y) and marking off the regions of positive and negative correlation, convince yourself that this (perhaps counter-intuitive) result is plausible.

The calculations of the various parameters of the distribution are straightforward (see Problem 16.29). The parameter A is determined by the normalization condition:  4   a a a a4 3 A(x 2 + y 2 ) dx dy = A + ⇒ A = 4. 1= 3 3 2a 0 0 The two expectation values required are given by  a a Ax(x 2 + y 2 ) dx dy E[X] = 0 0  5  a 3 a5 5a = 4 + = , 2a 4×1 2×3 8  a a 2 Ax 2 (x 2 + y 2 ) dx dy E[X ] = 0 0   6 a6 7a 2 a 3 + = . = 4 2a 5×1 3×3 15

(E[Y ] = E[X]),

Hence the variance, calculated from the general result V [X] = E[X 2 ] − (E[X])2 , is  2 5a 73 2 7a 2 − a , = V [X] = 15 8 960

230

Probability

and the standard deviations are given by

'

73 a. 960 To obtain the correlation coefficient we need also to calculate the following:  a a Axy(x 2 + y 2 ) dx dy E[XY ] = 0 0   6 3 a6 3a 2 a = 4 + = . 2a 4×2 2×4 8 σX = σY =

Then the covariance, given by Cov [X, Y ] = E[XY ] − E[X]E[Y ], is evaluated as 3 2 5a 5a a2 a − =− . 8 8 8 64 Combining this last result with the standard deviations calculated above, we then obtain Cov [X, Y ] =

Corr [X, Y ] = 

15 −(a 2 /64)  =− . 73 73 73 a 960 a 960

As the means of both X and Y are 58 a = 0.62a, the areas of the square of side a for which X − μX and Y − μY have the same sign (i.e. regions of positive correlation) are about (0.62)2 ≈ 39% and (0.38)2 ≈ 14% of the total area of the square. The regions of negative correlation occupy some 47% of the square. However, f (x, y) = A(x 2 + y 2 ) favors the regions where one or both of x and y are large and close to unity. Broadly speaking, this gives little weight to the region in which both X and Y are less than their means, and so, although it is the largest region in area, it contributes relatively little to the overall correlation. The two (equal area) regions of negative correlation together outweigh the smaller high probability region of positive correlation in the top right-hand corner of the square; the overall result is a net negative correlation coefficient.

17

Statistics

17.1 A group of students uses a pendulum experiment to measure g, the acceleration of free fall, and obtains the following values (in m s−2 ): 9.80, 9.84, 9.72, 9.74, 9.87, 9.77, 9.28, 9.86, 9.81, 9.79, 9.82. What would you give as the best value and standard error for g as measured by the group?

We first note that the reading of 9.28 m s−2 is so far from the others that it is almost certainly in error and should not be used in the calculation. The mean of the ten remaining values is 9.802 and the standard deviation of the sample about its mean is 0.04643. After including Bessel’s correction factor, the estimate of the population s.d. is σ = 0.0489, leading to a √ s.d. in the measured value of the mean of 0.0489/ 10 = 0.0155. We therefore give the best value and standard error for g as 9.80 ± 0.02 m s−2 . 17.3 The following are the values obtained by a class of 14 students when measuring a physical quantity x: 53.8, 53.1, 56.9, 54.7, 58.2, 54.1, 56.4, 54.8, 57.3, 51.0, 55.1, 55.0, 54.2, 56.6. (a) Display these results as a histogram and state what you would give as the best value for x. (b) Without calculation, estimate how much reliance could be placed upon your answer to (a). (c) Data books give the value of x as 53.6 with negligible error. Are the data obtained by the students in conflict with this?

(a) The histogram in Figure 17.1 shows no reading that is an obvious mistake and there is no reason to suppose other than a Gaussian distribution. The best value for x is the arithmetic mean of the 14 values given, i.e. 55.1. (b) We note that 11 values, i.e. approximately two-thirds of the 14 readings, lie within ±2 bins of the mean. This estimates the s.d. for the population as 2.0 and gives a standard √ error in the mean of ≈ 2.0/ 14 ≈ 0.6. (c) Within the accuracy we are likely to achieve by estimating σ for the sample by eye, the value of Student’s t is (55.1 − 53.6)/0.6, i.e. about 2.5. With 14 readings there are 13 degrees of freedom. From standard tables for the Student’s t-test, C13 (2.5) ≈ 0.985. It is therefore likely at the 2 × 0.015 = 3% significance level that the data are in conflict with the accepted value. [ Numerical analysis of the data, rather than a visual estimate, gives the lower value 0.51 for the standard error in the mean and implies that there is a conflict between the data and the accepted value at the 1.0% significance level. ] 231

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Statistics

2σ est

50

55

60

mean = 55.1

Figure 17.1 Histogram of the data in Problem 17.3.

17.5 A population contains individuals of k types in equal proportions. A quantity X has mean μi amongst individuals of type i and variance σ 2 , which has the same value for all types. In order to estimate the mean of X over the whole population, two schemes are considered; each involves a total sample size of nk. In the first the sample is drawn randomly from the whole population, whilst in the second (stratified sampling) n individuals are randomly selected from each of the k types. Show that in both cases the estimate has expectation 1 μi , k i=1 k

μ=

but that the variance of the first scheme exceeds that of the second by an amount 1  (μi − μ)2 . k 2 n i=1 k

(i) For the first scheme the estimator μˆ has expectation

μ ˆ =

nk 1  xj , nk j =1

where 1 μi for all j , xj  = k i=1 k

233

Statistics

since the k types are in equal proportions in the population. Thus, nk k k 1 1 1 μ ˆ = μi = μi = μ. nk j =1 k i=1 k i=1

The variance of μˆ is given by V [μ] ˆ =

1 n2 k 2

nk V [x]

1 (x 2  − μ2 ) nk  k  1 2 1 2 x  − μ , = nk k i=1 i =

again since the k types are in equal proportions in the population. Now we use the relationship σ 2 = xi2  − μ2i to replace xi2  for each type, noting that 2 σ has the same value in each case. The expression for the variance becomes   k  1  2 1 2 2 μ +σ −μ V [ μˆ ] = nk k i=1 i k 1  σ 2 − μ2 + 2 (μi − μ + μ)2 = nk nk i=1

=

k σ 2 − μ2 1  + 2 (μi − μ)2 + 2μ(μi − μ) + μ2 nk nk i=1

=

k kμ2 1  σ 2 − μ2 (μi − μ)2 + 0 + 2 + 2 nk nk i=1 nk

=

k 1  σ2 + 2 (μi − μ)2 . nk nk i=1

(ii) For the second scheme the calculations are more straightforward. The expectation k −1 value of the estimator μˆ = (nk) i=1 xi  is μ ˆ =

k k 1  1 nμi = μi = μ, nk i=1 k i=1

whilst the variance is given by V [ μˆ ] =

k k σ2 1  1  2 1 kσ 2 = , V [ x  ] = nσ = i i n2 k 2 i=1 n2 k 2 i=1 k2 n kn

since σi2 = σ 2 for all i.

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Statistics

Comparing the results from (i) and (ii), we see that the variance of the estimator in the first scheme is larger by k 1  (μi − μ)2 . nk 2 i=1

17.7 According to a particular theory, two dimensionless quantities X and Y have equal values. Nine measurements of X gave values of 22, 11, 19, 19, 14, 27, 8, 24 and 18, whilst seven measured values of Y were 11, 14, 17, 14, 19, 16 and 14. Assuming that the measurements of both quantities are Gaussian distributed with a common variance, are they consistent with the theory? An alternative theory predicts that Y 2 = π 2 X; are the data consistent with this proposal?

On the hypothesis that X = Y and both quantities have Gaussian distributions with a common variance, we need to calculate the value of t given by   N1 N2 1/2 w¯ − ω t= , σˆ N1 + N2 where w¯ = x¯1 − x¯2 , ω = μ1 − μ2 = 0 and  1/2 N1 s12 + N2 s22 σˆ = . N1 + N2 − 2 The nine measurements of X have a mean of 18.0 and a value for s 2 of 33.33. The corresponding values for the seven measurements of Y are 15.0 and 5.71. Substituting these values gives   9 × 33.33 + 7 × 5.71 1/2 = 4.93, σˆ = 9+7−2   18.0 − 15.0 − 0 9 × 7 1/2 = 1.21. t= 4.93 9+7 This variable follows a Student’s t-distribution for 9 + 7 − 2 = 14 degrees of freedom. Interpolation in standard tables gives C14 (1.21) ≈ 0.874, showing that a larger value of t could be expected in about 2 × (1 − 0.874) = 25% of cases. Thus no inconsistency between the data and the first theory has been established. For the second theory we are testing Y 2 against π 2 X; the former will not be Gaussian distributed and the two distributions will not have a common variance. Thus the best we can do is to compare the difference between the two expressions, evaluated with the mean values of X and Y , against the estimated error in that difference. The difference in the expressions is (15.0)2 − 18.0π 2 = 47.3. The error in the difference between the functions of Y and X is given approximately by V (Y 2 − π 2 X) = (2Y )2 V [ Y ] + (π 2 )2 V [ X ] 5.71 33.33 = (30.0)2 + (π 2 )2 7−1 9−1 = 1262 ⇒ σ ≈ 35.5.

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Statistics

The difference is thus about 47.3/35.5 = 1.33 standard deviations away from the theoretical value of 0. The distribution will not be truly Gaussian but, if it were, this figure would have a probability of being exceeded in magnitude some 2 × (1 − 0.908) = 18% of the time. Again no inconsistency between the data and theory has been established. 17.9 During an investigation into possible links between mathematics and classical music, pupils at a school were asked whether they had preferences (a) between mathematics and English, and (b) between classical and pop music. The results are given below.

Mathematics None English

Classical

None

Pop

23 17 30

13 17 10

14 36 40

Determine whether there is any evidence for (a) a link between academic and musical tastes, and (b) a claim that pupils either had preferences in both areas or had no preference. You will need to consider the appropriate value for the number of degrees of freedom to use when applying the χ 2 test.

We first note that there were 200 pupils taking part in the survey. Denoting no academic preference between mathematics and English by NA and no musical preference by NM, we draw up an enhanced table of the actual numbers mXY of preferences for the various combinations that also shows the overall probabilities pX and pY of the three choices in each selection.

M NA E Total pY

C

NM

P

Total

pX

23 17 30 70 0.35

13 17 10 40 0.20

14 36 40 90 0.45

50 70 80 200

0.25 0.35 0.40

(a) If we now assume the (null) hypothesis that there are no correlations in the data and that any apparent correlations are the result of statistical fluctuations, then the expected number of pupils opting for the combination X and Y is nXY = 200 × pX × pY . A table of nXY is as follows:

M NA E Total

C

NM

P

Total

17.5 24.5 28 70

10 14 16 40

22.5 31.5 36 90

50 70 80 200

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Statistics

Taking the standard deviation as the square root of the expected number of votes for each particular combination, the value of χ 2 is given by 



χ2 =

all XY combinations

ni − mi √ ni

2 = 12.3.

For an n × n correlation table (here n = 3), the (n − 1) × (n − 1) block of entries in the upper left can be filled in arbitrarily. But, as the totals for each row and column are predetermined, the remaining 2n − 1 entries are not arbitrary. Thus the number of degrees of freedom (d.o.f.) for such a table is (n − 1)2 , here 4 d.o.f. From tables, a χ 2 of 12.3 for 4 d.o.f. makes the assumed hypothesis less than 2% likely, and so it is almost certain that a correlation between academic and musical tastes does exist. (b) To investigate a claim that pupils either had preferences in both areas or had no preference, we must combine expressed preferences for classical or pop into one set labeled PM meaning “expressed a musical preference”; similarly for academic subjects. The correlation table is now a 2 × 2 one and will have only one degree of freedom. The actual data table is

PA NA Total pY

PM

NM

Total

pX

107 53 160 0.80

23 17 40 0.20

130 70 200

0.65 0.35

and the expected (nXY = 200pX pY ) one is

PA NA Total

PM

NM

Total

104 56 160

26 14 40

130 70 200

The value of χ 2 is

χ2 =

(3)2 (3)2 (−3)2 (−3)2 + + + = 1.24. 104 26 56 14

This is close to the expected value (1) of χ 2 for 1 d.o.f. and is neither too big nor too small. Thus there is no evidence for the claim (or for any tampering with the data!).

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Statistics

17.11 A particle detector consisting of a shielded scintillator is being tested by placing it near a particle source whose intensity can be controlled by the use of absorbers. It might register counts even in the absence of particles from the source because of the cosmic ray background. The number of counts n registered in a fixed time interval as a function of the source strength s is given as: source strength s: counts n:

0 6

1 11

2 20

3 42

4 44

5 62

6 61

At any given source strength, the number of counts is expected to be Poisson distributed with mean n = a + bs, where a and b are constants. Analyze the data for a fit to this relationship and obtain the best values for a and b together with their standard errors. (a) How well is the cosmic ray background determined? (b) What is the value of the correlation coefficient between a and b? Is this consistent with what would happen if the cosmic ray background were imagined to be negligible? (c) Do the data fit the expected relationship well? Is there any evidence that the reported data “are too good a fit”?

Because in this problem the independent variable s takes only consecutive integer values, we will use it as a label i and denote the number of counts corresponding to s = i by ni . As the data are expected to be Poisson distributed, the best estimate of the variance of each reading is equal to the best estimate of the reading itself, namely the actual √ measured value. Thus each reading ni has an error of ni , and the covariance matrix N takes the form N = diag(n0 , n1 , . . . , n6 ), i.e. it is diagonal, but not a multiple of the unit matrix. The expression for χ 2 is

χ 2 (a, b) =

 6   ni − a − bi 2 √ ni i=0

(∗).

Minimization with respect to a and b gives the simultaneous equations

0=

6  ∂χ 2 ni − a − bi , = −2 ∂a ni i=0

0=

6  ∂χ 2 i(ni − a − bi) . = −2 ∂b ni i=0

As is shown more generally in textbooks on numerical computing (e.g. William H. Press et al., Numerical Recipes in C, 2nd edn (Cambridge: Cambridge University Press, 1996), Sect. 15.2), these equations are most conveniently solved by defining the

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Statistics

quantities S≡

Sxx

6  1 , n i=0 i

6  i2 ≡ , n i=0 i

Sx ≡

6  i , n i=0 i

Sxy ≡

Sy ≡

i=0

6  ini i=0

ni

6  ni

,

ni

,

 ≡ SSxx − (Sx )2 .

With these definitions (which correspond to the quantities calculated and accessibly stored in most calculators programmed to perform least-squares fitting), the solutions for the best estimators of a and b are Sxx Sy − Sx Sxy ,  Sxy S − Sx Sy bˆ = , 

aˆ =

with variances and covariance given by σa2 =

Sxx , 

σb2 =

S , 

Cov (a, b) = −

Sx . 

The computed values of these quantities are: S = 0.38664; Sx = 0.53225; Sy = 7; Sxx = 1.86221; Sxy = 21;  = 0.43671. ˆ bˆ and the variances σa2 and σb2 are From these values, the best estimates of a, aˆ = 4.2552,

bˆ = 10.061,

σa2 = 4.264,

σb2 = 0.8853.

The covariance is Cov (a, b) = −1.2187, giving estimates for a and b of a = 4.3 ± 2.1

and

b = 10.06 ± 0.94,

with a correlation coefficient rab = −0.63. (a) The cosmic ray background must be present, since n(0) = 0, but its value of about 4 is uncertain to within a factor of 2. (b) The correlation between a and b is negative and quite strong. This is as expected since, if the cosmic ray background represented by a were reduced towards zero, then b would have to be increased to compensate when fitting to the measured data for non-zero source strengths. (c) A measure of the goodness-of-fit is the value of χ 2 achieved using the best-fit values for a and b. Direct resubstitution of the values found into (∗) gives χ 2 = 4.9. If the weight of a particular reading is taken as the square root of the predicted (rather than the measured) value, then χ 2 rises slightly to 5.1. In either case the result is almost exactly that “expected” for 5 d.o.f. – neither too good nor too bad. There are five degrees of freedom because there are seven data points and two parameters have been chosen to give a best fit.

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Statistics

17.13 The following are the values and standard errors of a physical quantity f (θ ) measured at various values of θ (in which there is negligible error): θ f (θ )

0 3.72 ± 0.2

π/6 1.98 ± 0.1

π/4 −0.06 ± 0.1

π/3 −2.05 ± 0.1

θ f (θ )

π/2 −2.83 ± 0.2

2π/3 1.15 ± 0.1

3π/4 3.99 ± 0.2

π 9.71 ± 0.4

Theory suggests that f should be of the form a1 + a2 cos θ + a3 cos 2θ . Show that the normal equations for the coefficients ai are 481.3a1 + 158.4a2 − 43.8a3 = 284.7, 158.4a1 + 218.8a2 + 62.1a3 = −31.1, −43.8a1 + 62.1a2 + 131.3a3 = 368.4. (a) If you have matrix inversion routines available on a computer, determine the best values and variances for the coefficients ai and the correlation between the coefficients a1 and a2 . (b) If you have only a calculator available, solve for the values using a Gauss–Seidel iteration and start from the approximate solution a1 = 2, a2 = −2, a3 = 4.

Assume that the measured data have uncorrelated errors. The quoted errors are not all equal and so the covariance matrix N, whilst being diagonal, will not be a multiple of the unit matrix; it will be

N = diag(0.04, 0.01, 0.01, 0.01, 0.04, 0.01, 0.04, 0.16).

Using as base functions the three functions h1 (θ) = 1, h2 (θ) = cos θ and h3 (θ) = cos 2θ, we calculate the elements of the 8 × 3 response matrix Rij = hj (θi ). To save space we display its 3 × 8 transpose: ⎛

1 1 RT = ⎝ 1 0.866 1 0.500

1 1 0.707 0.500 0 −0.500

⎞ 1 1 1 1 0 −0.500 −0.707 −1 ⎠ . −1 −0.500 0 1

Then ⎛

RT N−1

⎞ 25 100 100 100 25 100 25 6.25 50 0 −50 −17.7 −6.25 ⎠ = ⎝ 25 86.6 70.7 25 50.0 0 −50.0 −25 −50 0 6.25

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Statistics

and



⎞ 1 1 1 ⎜1 0.866 0.500 ⎟ ⎜ ⎟ ⎜1 0.707 0⎟ ⎜ ⎟ ⎜ 0.500 −0.500 ⎟ T −1 T −1 ⎜ 1 ⎟ R N R=R N ⎜ 0 −1 ⎟ ⎜1 ⎟ ⎜ 1 −0.500 −0.500 ⎟ ⎜ ⎟ ⎝ 1 −0.707 0⎠ 1 −1 1 ⎛ ⎞ 481.25 158.35 −43.75 = ⎝ 158.35 218.76 62.05 ⎠ . −43.75 62.05 131.25

From the measured values, f = (3.72, 1.98, −0.06, −2.05, −2.83, 1.15, 3.99, 9.71)T , we need to calculate RT N−1 f, which is given by



25 100 ⎝ 25 86.6 25 50.0

100 100 70.7 50 0 −50



⎞ 3.72 ⎜ 1.98 ⎟ ⎜ ⎟ ⎞ ⎜ −0.06 ⎟ ⎜ ⎟ 25 100 25 6.25 ⎜ ⎟ −2.05 ⎟ 0 −50 −17.7 −6.25 ⎠ ⎜ ⎜ −2.83 ⎟ , ⎜ ⎟ −25 −50 0 6.25 ⎜ ⎟ ⎜ 1.15 ⎟ ⎝ 3.99 ⎠ 9.71

i.e. (284.7, −31.08, 368.44)T . The vector of LS estimators of ai satisfies RT N−1 Raˆ = RT N−1 f. Substituting the forms calculated above into the two sides of the equality gives the set of equations stated in the question. (a) Machine (or manual!) inversion gives ⎛ ⎞ 3.362 −3.177 2.623 (RT N−1 R)−1 = 10−3 ⎝−3.177 8.282 −4.975⎠ . 2.623 −4.975 10.845 From this (covariance matrix) we can calculate the standard errors on the ai from the square roots of the terms on the leading diagonal as ±0.058, ±0.091 and ±0.104. We can further calculate the correlation coefficient r12 between a1 and a2 as −3.177 × 10−3 = −0.60. 0.058 × 0.091 The best values for the ai are given by the result of multiplying the column matrix (284.7, −31.08, 368.44)T by the above inverted matrix. This yields (2.022, −2.944, 4.897)T to give the best estimates of the ai as r12 =

a1 = 2.02 ± 0.06,

a2 = −2.99 ± 0.09,

a3 = 4.90 ± 0.10.

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Statistics

(b) Denote the given set of equations by Aa = b and start by dividing each equation by the quantity needed to make the diagonal elements of A each equal to unity; this produces Ca = d. Then, writing C = I − F yields the basis of the iteration scheme, an+1 = Fan + d. We use only the simplest form of Gauss–Seidel iteration (with no separation into upper and lower diagonal matrices). The explicit form of Ca = d is ⎞ ⎛ ⎞⎛ ⎞ ⎛ 0.5916 1 0.3290 −0.0909 a1 ⎝ 0.7239 1 0.2836 ⎠ ⎝ a2 ⎠ = ⎝ −0.1421 ⎠ 2.8072 a3 −0.3333 0.4728 1 and



⎞ 0 −0.3290 0.0909 0 −0.2836⎠ . F = ⎝−0.7239 0.3333 −0.4728 0

Starting with the approximate solution a1 = 2, a2 = −2, a3 = 4 gives as the result of the first ten iterations a1

a2

a3

2.000 1.613 1.890 1.856 1.943 1.947 1.980 1.987 2.000 2.005 2.011

−2.000 −2.724 −2.563 −2.824 −2.804 −2.899 −2.907 −2.944 −2.953 −2.969 −2.975

4.000 4.419 4.633 4.649 4.761 4.781 4.827 4.842 4.861 4.870 4.879

This final set of values is in close agreement with that obtained by direct inversion; in fact, after 18 iterations the values agree exactly to three significant figures. Of course, using this method makes it difficult to estimate the errors in the derived values.